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Jörn Menninger

Building Secure AI Solutions: A Deep Dive with Omnifact's Patrick Helmig



Executive Summary

In this episode of Startuprad.io, host Jörn "Joe" Menninger interviews Patrick Helmig, Co-Founder and CEO of Omnifact. They discuss the rapid evolution of AI in Europe, focusing on GDPR-compliant, self-hosted models and the future of affordable AI solutions. Patrick highlights Omnifact’s role in enabling AI adoption in regulated industries, emphasizing the importance of secure, efficient integration. They also explore key use cases, like banking and property management, while addressing data privacy challenges. The episode wraps up with insights into future developments, including Patrick’s plans for funding and hiring to expand Omnifact's capabilities.




Introduction

Hello, and welcome to another episode of Startuprad.io, your podcast covering the latest in startup news and trends from Germany. I'm your host, Jörn "Joe" Menninger, and today, I'm thrilled to bring you an insightful conversation with Patrick Helmig, the Co-Founder and CEO of Omnifact. 

In this episode, we dive into the evolving landscape of AI and its transformative potential for businesses, especially in highly regulated industries like banking, insurance, and pharma. Patrick shares the journey of Omnifact, from its inception sparked by the introduction of GPT-3, to developing customized AI solutions that prioritize data privacy and security. We'll discuss the challenges and opportunities in local model hosting in Europe, the future of AI models, and how Omnifact is paving the way for more efficient automation and knowledge management.

Stay tuned as we explore how Omnifact assists companies in automating complex processes, managing extensive documentation, and integrating AI seamlessly within their infrastructure. We also touch on Omnifact's future plans, including investment goals and hiring needs, along with Patrick's insights on improving the startup ecosystem in Frankfurt.

This episode is sponsored by Hessen Trade and Invest. Let's get started!

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The Video Podcast is set to go live on Thursday, September 19th, 2024





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Interview Highlights


Questions Discussed in the Interview:

  1. European Model Hosting   - How does hosting AI models locally in Europe under GDPR compliance provide competitive advantages compared to relying on international cloud providers?

  2. Self-Hosted Models   - What are the primary benefits and challenges for large organizations in licensing and running AI models within their own infrastructure?

  3. MITA Models   - Can you explain the performance capabilities of MITA's 3.1 models and why they are suitable for integration within company infrastructures?

  4. Future of AI Models   - What potential benefits might smaller, more affordable AI models offer for solving significant use cases without requiring the largest models available?

  5. Hybrid Approach   - How do you envision a future where both self-hosted and public AI models coexist, and what impact might this have on data security and operational efficiency?

  6. Virtual Augmented Generation   - For what types of use cases might virtual augmented generation, where models use language capabilities with provided information, be most effective and sufficient?

  7. Bank Use Case   - In the context of the banking industry, how does AI assist in managing extensive process documentation required by regulatory bodies, and what efficiencies does it bring?

  8. Live System Access   - What are the potential advantages and technical hurdles in enabling AI systems to access and utilize live system data for more accurate and timely responses?

  9. Sales Automation   - How can AI-driven automation streamline sales processes, from data entry to follow-up tasks, and what are the long-term benefits for sales teams?

  10. Investment and Hiring    - What strategic goals is Omnifact aiming to achieve with their planned pre-seed and seed funding rounds, and how will they prioritize hiring in areas such as communications, marketing, sales, and engineering to support these goals?


Key Takeaways from the Interview:


Introduction and Atmosphere:

  • Host: Jörn "Joe" Menninger, CEO and Founder of Startuprad.io

  • Guest: Patrick Helmig, Co-Founder and CEO of Omnifact

  • Episode sponsored by Hessen Trade and Invest

  • Acknowledgment of rescheduled recording due to illness

  • Background meeting and past startup event connections


Patrick Helmig's Background:

  • Developer by training with a degree in computer science

  • Early career in network security, boosting business post-Snowden revelations

  • First startup (Secdash) failed commercially but was valuable as a learning experience

  • Co-founded Rocketloop with Florian and Alex, transitioning from project-based work to product focus


Formation and Evolution of Omnifact:

  • Sparked by the introduction of GPT-3, shifting focus to AI product development

  • Goal to enable secure, efficient AI adoption in highly regulated industries (banks, insurance, medtech, pharma)

  • Struggled with client concerns over compliance, security, and data privacy


Omnifact's Solutions and Services:

  • Focus on European Model Hosting to ensure GDPR compliance

  • Self-hosted model capabilities for large organizations

  • Use of MITA's 3.1 for high-performance internal models

  • Providing tools and capabilities such as web search, web browsing, and a plugin system for API calls

  • AI assisting with documentation management in banks and building landlords

  • Live system data integration for accurate AI responses

  • Automating processes such as customer complaints and sales follow-up tasks


Future of AI Models:

  • Predicts a mix of self-hosted and public models

  • Smaller, affordable models could solve major use cases

  • The importance of fine-tuning base models for specific needs remains uncertain

  • Virtual augmented generation might suffice for most use cases


Challenges and Industry Insights:

  • Difficulty in building own models due to financial constraints

  • The necessity of addressing control and data issues, ensuring GDPR compliance

  • Creating flexible AI solutions that work with multiple cloud providers and support self-hosted models

  • Dealing with highly regulated industries requiring specific data privacy measures


Investment and Hiring Plans:

  • Planning a pre-seed round by the end of the year, seed round next year

  • Looking to hire in communications, marketing, sales, and engineering

  • Interested in discussions with institutional investors


Suggestions for Local Decision Makers:

  • Feedback requested on existing startup support

  • Suggestions for improving sustainability and support for startups in the local region


Closing Remarks:

  • Joe and Patrick exchange thanks and farewells

  • Joe wishes Patrick good luck with Omnifact


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About the Guest

In this episode of "Startuprad.io," we are honored to have Patrick Helmig (https://www.linkedin.com/in/patrick-helmig-3732a74a/), the Co-Founder and CEO of Omnifact (https://omnifact.ai/de), as our guest. Patrick is a seasoned developer with a rich background in computer science, having initially studied law and business before dedicating himself to the tech world. His early career in network security, particularly in pen testing and social engineering, set a strong foundation for his entrepreneurial journey. Patrick's first startup, Secdash, although not commercially successful, provided valuable learning experiences that shaped his future endeavors. Meeting his current co-founders, Florian and Alex, during the Secdash period, eventually led to the formation of Rocketloop—a boutique firm specializing in creating digital products for both startups and larger organizations.

The transformative moment for Patrick and his team came with the introduction of GPT-3, which inspired a pivot towards product development and the creation of Omnifact. Established in Frankfurt, Omnifact is at the forefront of enabling AI adoption across highly regulated industries such as banking, insurance, medtech, and pharmaceuticals. As the CEO, Patrick focuses on addressing the compliance and security concerns that often accompany AI integration, offering solutions that range from self-hosted models to hybrid approaches. Omnifact's platform aims to provide organizations with the flexibility to adopt AI technologies securely and efficiently, ensuring that data privacy and regulatory requirements are met without sacrificing innovation.


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Jörn ‘Joe’ Menninger is the founder and host of Startuprad.io. He has worked more than 12 years with household names in consulting, in financial services and startup services, as well as a startup scout. With a passion for uncovering the next big thing in tech, Joe brings deep insights and thought-provoking questions to every interview. Connect with Joe on LinkedIn and Twitter.



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Automated Transcript

Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:00:02]:

Hello and welcome everybody. This is Joe from startupbreak. Io, your startup podcast and YouTube blog from Germany. Today, I welcome another guest in our interview series sponsored by Hassan Trade and Invest. I would like to welcome Patrick here from Frankfurt. Hey. How you doing?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:00:19]:

Hey, Joel. Thanks. I'm feeling great, and I'm very happy to be here.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:00:24]:

It's good that you feel great because we had to move a little bit our recording due to me being sick, you being sick. And now, finally, we made it. I I I think after 8 weeks?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:00:36]:

Something like that. Yes. I I


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:00:37]:

Something like that. Yes. Great. Let's talk a little bit about our enabler, h t a I, and the enterprise Europe network, Hessen. This recording was made possible by h t a I and the enterprise Europe network, Hessen. These organizations have made tremendous contributions to helping start up businesses succeed and thrive, providing a range of services from helping to find grants to ongoing partnerships. By taking advantage of these resources, start up companies can network and develop innovative strategies for success on the international stage. The dedicated support of HDIA and the EEN Hessen is paramount in providing startup businesses with the tools for lasting success.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:01:19]:

You can learn more in the links down here in the show notes. So, Patrick, we we met in the past, we have realized. And and if we're talking about the past, I mean, like ancient times and time in terms of the stutter world. Right?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:01:36]:

Absolutely. Like, I I I I if I recall correctly, we met at the, startup week, in Frankfurt. That must have been over 10 years ago, something like that.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:01:49]:

I think it was startup weekend, like 9 years ago, but no big difference at all.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:01:54]:

It's a it's a fun fact fun fact that I I found my first cofounder from a very first startup at this very startup week. That was actually, like, really my kickoff into the startup world and being a founder.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:02:09]:

Big mental high five to Mario Hachma, one of our cohosts who actually organized this startup weekend. Thank you very much.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:02:16]:

We shout out to Mario in any case. He's he's awesome.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:02:21]:

Yes. Today, we are here to talk a little bit about, who you are, what you did, and OmniFACT, an AI startup. But first, I was going a little bit through your CV, and I see you are actually a developer at heart. Is that true?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:02:42]:

That is true. That is true. I studied, computer science and, business, but I only finished computer science.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:02:51]:

And you you've done a little bit, financial analyst, working student, student worker. But then from what I can see, you've been an entrepreneur, all your professional life going back to 2012. Is that true?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:03:08]:

That's true. That's true. I I I so so I I studied law for, like, 1 semester, then I saw that that wasn't for me. Then then I did what I loved, became a programmer, then I find out then I thought I had to study something. Then I started business, which kinda bored me. So I went to computer science. And during my studies, I started a small boutique for, pen testing actually, and and and social engineering was actually came from the hackers team and the security scene in the very beginning.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:03:46]:

And what did you do there, and are you currently social engineering us?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:03:53]:

If I if I would tell you, Thurman, where would be the fun? What we did there was basically, we we tried to help, like, mid sized German companies to secure their network, and we especially helped, executives who start, general to countries like Israel, China, Japan, Middle East, where you have actual risks of being, targeted by, state actors or large organizations, to to be more secure in their travels, and their daily lives. And we were really lucky. We started, I think, like, 4 weeks in or 8 weeks in, Snowden came out, and that that basically was the best push for any start starting business you could imagine.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:04:44]:

I see. And then at one point, you started building AI and software solutions for other people.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:04:51]:

That yes. So so so from there, I I after the start of the week, I made Khan, which still is a great friend of mine, with whom I started Secdash, which was, like, a little bit between today and the past. It was a a startup to monitor the chatter of IT security issues in the dark dark web and IRC channels and so on to basically get an early warning system for new attacks on websites, on servers, and so on. And that was actually the point where, for the first time, worked with natural language processing. So that basically was the first time was working with the technologies that later became what we clearly call, AI. And that that startup failed miserably on the business side, but it was a great learning experience. And during that time, I met Florian, and Alex. Florian, both I'm still working with both.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:05:54]:

Florian Kurismeg, my cofounder at Omnifact. Alex was part of the founding team. And from from meeting these 2, we we got into building Rocketloop, which was like a boutique for building digital products for well funded startups, and, larger organizations. And I think the past 7 or 8 years, we mostly built first of all, it was called data science. That was called machine learning. Now it's called AI. But, basically, state of the art, machine learning AI implementations, but on project basis, there was we didn't have a product at this time.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:06:38]:

And how so so Rocketloop is still around the company. You you spoke about it in the past, but Rocketloop is still around and you're still working there as the CEO. What was kind of the kick off the the the spark that made you start Omnifact?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:06:56]:

Good question. There were there were 2 sparks actually. First of all, Florida, we we always wanted to to to to transist from being in a project company to a product company. And, when GPT 3 came out, it was a little bit before JetGPT. Florence showed it to me, and I was like, okay. We can basically forget that we're gonna do, like, individual natural language processing, projects in the next few years. So we really have to get thinking and have to find a way around that. And at that point, this point is was more like being sure that our group is okay rather than actively searching for a product.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:07:39]:

And then we went to our customers. And as you know, we are located in Frankfurt. So so most of our customers are in highly regulated interest industries. We work with banks, insurance companies, medtech companies, pharma companies. All these have, like, very high standard, but status when it comes to, where they can put their data, how how they can use their data in certain context, how they have to be conscious about data privacy and so on. And we we went to them, like, a little little bit provocative and said like, look at this. We have a cool demo with gpt, 3 at this time. When when are we going to automate your customer service based on that? And then, first of all, they were very, like, excited.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:08:27]:

We did some, prototypes, but then we talked to the, compliance and information security people, and they were, like, very not so happy. Having a single supplier risk would open my eye, sending everything to the US was was just already for prime time. And that was, first of all, little bit of downer, but that was basically the start of Flora and me thinking, oh, maybe there is a chance to build a product that enables organizations to use this kind of technologies to automate their daily business process. Mhmm.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:09:03]:

I see. So let's talk a little bit about OmniFACT. We already know it's, what what natural language processing model is behind it?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:09:15]:

So, Onifect Onifect, more or less, we see Onifect as a platform that enables AI adoption, across companies. And allow me to to to to to to, circle a little bit back. So, I think we all have heard so much about AI and there's like McKinsey had a study in May where they said we can automate up to 30% of all business processes in Europe with AI. But as you know or as everyone sees is that there's very little to show for it right now. Right? There's Klarna, who has one good example how they automated their their customer service. But beyond that, there are not many cases where we actually have great AI solutions in production right now.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:09:57]:

I actually have to admit, I'm currently, in a little bit of discussion with Google Ads and it appears they only have chatbots there anymore and they reply always with the same stuff. But I'm a special case because I'm a freelancer working on the brand of sort of radio, which completely by, which completely throws out the rules even though it's very legal here in Germany. And therefore, they are doing nothing else than repeatedly sending me always the same message. Yeah. Do it with an exact with exact a has to match exactly b. I can do it. Yes. Do do it again.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:10:35]:

A has to match exactly b. I can't do that. So so you always get the same message back and it feels like, you're bumping you're bumping your hand on the wall. So there there's good customer service with AI and there's very bad customer service with AI. But I have to admit, I expected more from Google.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:10:58]:

I think I think I think to be fair, Google is like a large organization, and I think they were, like, prohibited to use Gemini for a long time in their processes. So I think there's a good chance that this will change soon. But but to circle back to your question, we we we try to to solve the issues that prevent companies from adopting AI and and building solutions like good serve good customer services, really individual has access to the CRM, to the product information, and so on. And you can bundle this to to give you, like, a very, personalized experience. But to do so, we actually think it's a bad idea to focus on only 1 l m provider. So what we do is, basically, we have the possibilities to work with all cloud providers. So Atropic, Google, Open My Eye, and all Azure based models. But we also support self hosted models.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:11:53]:

And that that actually gives gives us quite a bit of flexibility, to basically choose the right model for a job. Because, of course, if you want to write, marketing content for set up radio, you probably want to have access to the most powerful model, and you don't have to think about data privacy in any way. But if if you That's


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:12:16]:

because apparently, the podcast is meant to be published. Right?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:12:20]:

Absolutely. Absolutely. So so if you if you work in this space, you could probably also work with Claude directly or JetGPT. But if you want to review, job applications, for example, this is not the case. There you have to be very sensitive when it comes to data privacy and how you process that. And if you're a large organization, you probably want to use private model that you host yourself maybe, just for these use cases. And what Omnifyc allows you is basically to set up, we call it spaces, like AI assistance that can automate certain processes and basically tie them to certain models. So you can basically set the data privacy, restrictions based on the use case you have.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:13:07]:

And additionally, you can then connect your internal data services also to these use cases, so you can make sure, okay, we we have our block database, and that is used to create a new block entry, but that can be used with the, like, best public model available. But our HR space is restricted to our local, LM that we run ourselves, or we have in our white, virtual private cloud. And but that can also interact with our and our, like, database of of applicants of FactSet. So that is that's the main idea, of our platform to basically cater to the needs of organizations, in a way that we, allows for every use case to have a conscious decision about the data privacy requirements, where you want your own information, and which of your systems and, data sources you may connect to this use case to make it more efficient to allow for more automation.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:14:07]:

I see. When we talked before, you said, that is, 3 highly highly regulated industries, and they have the usual headaches, control over the data, including data secrets and GDPR, connecting with proprietary systems, and, fast development in in in the new models and, overtake overtake actually the projects because, OpenAI can much better has more financial means to, really work on an AI model than any given company, out or most companies out there who are willing to do that.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:14:54]:

Absolutely. Absolutely. You basically you basically went down the list that that that there's actually now a pitch deck. So so so it's it's data control and security. Looks like you've seen it. If if you have that established, you can, can basically have your your, your data and services integrated, k, into some AI solution, and that allows you to to actually build meaningful automation steps. But you are absolutely right that it's if you would build our own models, it would be a David against Goliath case, but not not one you could win because that's a, playoff power and money right now. But the interesting thing is you have a few certain developments that are super interesting.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:15:38]:

First of all, you have companies like this trial, which do an extremely great job to build models here in Europe that are also available hosted in Europe by European entities. So you have the GPR thing covered. And they also allow large organizations to license their model and run the large models within the infrastructure. And in addition, you, of course, have MITA, which released the the 3 point one models, which are exceptionally well and also run within our in in company's infrastructure. Looking forward, I wouldn't be surprised if in the future, a lot of, like, mid sized models that can run on hardware that costs, I don't know, like, between 15 20 k to buy could solve very meaningful use cases. So so and once you have that established, I think the question will always be, do do I need the largest, most expensive, but also most closed and single provider restricted model for the use case I have? Or isn't the aren't most use cases solvable by smaller, cheaper models that I can control ourselves? And our guess is the future will be hybrid between, like, models you run within your infrastructure and public models, and and maybe some some things in between. I think it's still an open question how much fine tuning will play a role so that you have, like, a base model, like, for example, Lam of 3.1, and you want to be basically adapted to your use case or your language or your knowledge from from within the organization. If that plays a large role, then, again, you're gonna have self hosted models, which would be very important for us.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:17:35]:

Another way to include the company's or organization's information are are ways like virtual augmented generation where you basically, use the language capabilities of a model, but basically force it to base their answers based on information you provide them based on the query or the question user asks. And from what we have seen so far, it looks like that these solutions without fine tuning, without individual training are probably good enough for 80, 85, 90% of the of the use cases. And will be very interesting to see how this will progress as models improve. Because I think right now, no one has a good grasp of how great the GPT 5 grade models will be.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:18:24]:

That that is an interesting question. We we we have now doing a little bit philosophy. Can we get, really, down to business? What could a potential client that is listening right now actually do with their tools? Where can you apply it? Where do you have use cases where you can actually use the tools?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:18:51]:

Absolutely. Absolutely. So the the the very first use case that, works off the shelf and is is is very helpful for most organizations is basically knowledge management. Since you can use Omnifact to, make the information in your document managements, in your confluence, in your notion, and so on systems available through an an IS system, that is centralized at at one point, you can enable much better access to companies or organization companies or, information. Where we have seen this to be the most successful so far is within banks because they have something like and it's hard to translate. So they have to basically have a written version of every process that is relevant for the bank's organization. And they are normally organized by the department responsible for the for the process step, which leads to a document that has 1,000 to sometimes 10,000 of pages that are very hard to comprehend as as a person going through. But with with an AI system that can basically access the information and summarize it based on your question, we, can make this much more useful as a as source of information.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:20:18]:

And that's actually the first, like, high impact use case we have seen to actually make this process documentation that many organizations must have because of regulatory requirements to make them actually a powerful tool for their employees to access the information they need much faster.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:20:36]:

For everybody with no financial background, literally translates to written fixed order, which is documentation implying a structured or formalized system. And this formalized system basically tells you how to how you have to behave your processes as an employee in a bank in order to be compliant with the regulations. Plus, it also can be audited by the supervisor. Plus, it can also be, it you you can also be checked against this SFO, if you're really doing your stuff. And believe me, if the auditor does such a audit, commonly known as a, 54 audit, It's it's completely a fun freestone here. Believe me. That that that is the moment when every bank CEO goes


Patrick Helmig | Co-Founder | CEO | Omnifact [00:21:41]:

I I want to I want to share some some some information, like, some some context on that. Why why why this is so interesting and so hard? Because if you if you're not within the financial industry, having a documentation of process can't be so hard, can it? But the interesting thing about this strictly fix here to auto is you have many departments within within a bank, and every department is responsible for their process then. So, basically, if you want to describe the process of granting a loan to a customer, this will involve 6, 7, 8, 9 departments throughout the bank. One bank. And basically, you don't have one document that's grabbed the whole process, but you have one document for each process step. And that actually makes this documentation as it exists completely incomprehensible in many cases. But with the AI, you actually can now ask questions like, how do we organize our loan granting process? Who's responsible for that? Who handles the the risk assignment? How do we handle ESG risks in this process? And it will basically puzzle together the information from from hundreds of of documents to give you this explicit answer, which in the past would be very, very annoying to basically get to, like, get in get in a very compact way. And you probably would have to speak to 3 or 4 people who give you the right hints to basically find that out for yourself.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:23:13]:

Mhmm.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:23:15]:

I see. So, for example, written fixed order. That that's one you use case. Can you can you tell us, like a few others, what you can also do? Because this one is, I would say, pretty pretty much limited to European Financial Institutions.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:23:35]:

We have also, we have we've worked with 1, one of Germany's largest landlords, and they they have an interesting challenge. They they grew relatively fast, and not only organic. So basically, they bought together a lot of buildings and joined or merged certain companies. And this led to the fact that for every building they had, they have different kind of structures sometimes for the documentation about that building. So and if you now want to ask, like, when was the, when was the elevator last audited? And and was something found at the audit? Has it been fixed? You really have to dig into your document management system, find this kind of information. Sometimes through PDFs that are not, what we haven't run through OCR, so you can't really search for it. And we help them to basically build AI assistance for these buildings that you now can ask these questions. And this basically reduces the time that they they they have to get this information, from from minutes to seconds.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:24:42]:

That that is that that is not the use case. I'm I'm currently focusing a lot when I speak about the use cases on what we like, what is actually shipped right now. But to to extend it a tiny little bit. So currently, we focus a lot on, like, how we can make the information that a organization has and that's persistent. So something is in confluence in the document management system to make that accessible through an IaaS. But in parallel, we are currently working very hard on making, also giving, our AI systems access to live systems. So if you ask the only factor systems question, the first thing it asks itself is, what kind of tools do I have to answer your question? So and right now, it has 2 tools. It either can give you an answer directly if it's trivial, or it can go and ask a knowledge base, which basically is retrieved augmented generation implementation that basically gets you the information based on the the data source of where where where it is.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:25:40]:

But what we currently do is we gotta provide a number of additional tools. One one that I showed you a little bit before the call is we're gonna have web search and web browsing, which most people know from Jitsi. But what is more exciting is we're currently building something like a plug in system that allows you to create a tool that, for example, would do API calls to your customer relation management system or to your product information system. So and if you combine these tools, then you can very can automate very interesting things. Because then you can say, oh, I have this customer email and the customer complains about, I don't know, a broken, a broken piece of hardware that that they bought from you. You could basically then take this information, look up a new CEM, see if the customer actually bought it, when they bought it. Then you can go and check your knowledge base for the warranty, the warranty rules for this certain product, can check that against the time it was bought and can basically check if the customer would be eligible for for exchange. And that you can basically now automate end to end because our AI system can basically plan the steps.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:26:57]:

It will ask you, hey, Joe. This is the steps I would like to go. This is what I want to do. Provide you with an answer. Then you can say, no. I don't know. It's I know already it's it's beyond warranty. It's but, there there's a certain reason that we might may, exchange it anyways if it's from that product line, for example, be because we had issues with that.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:27:21]:

Then we'd change the plan, then we'd run the plan and give you the, like, the the complete answer. And these kind of, like, end to end automations that become possible once you have access to not only data, but also, like, systems within an organization. This is what excites excites us a lot because I think at this point, you can make people much more efficient.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:27:43]:

For example, what would be great if, at one point in the future, your sales employee meets somebody on a fair, to talk to his phone and says, okay, Offer this and that to this client. Get it ready for me in the draft. And then the next day, he's in office. He just has to review it and clicks it.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:28:02]:

Absolutely. I I have another example that that comes from our daily work. So so currently, with all larger customers, I still have, like, one to one calls to basically understand their needs, understand their use cases, and, really still learn also doing sales, but also to learn for us what what are interesting use cases. And after this call, I normally, I write I write down a lot. So after this call, I go to my CRM, basically put in what it's interesting, if it's an interesting lead, how large the organization is, and all this information. I go to our Slack channel and report back a little bit because it's very sometimes very exciting and interesting for our team to see what we're working on. Then I go to Notion and put in, if we have any feature requests that are new to us that we didn't have, or if they mentioned the feature request or feature that we don't have yet and add that. And then I I send them an email depending on how the the call was, with our product, presentation and and so on.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:29:03]:

And ideally ideally, I would like to just put all the things I wrote down in OmniFx and OmniFx would understand. Oh, I see. This customer is interesting to us. It has, this potential of seeds. They want to test with that. I'm gonna put this into the CRM. They also mentioned this in this feature request. We have that in Notion ready.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:29:23]:

Let me update that for you. And, also, here's a summary I would like to set to Slack, and is it okay for me to send this email to this? So so and if if we get this point, like, my life and the life of million of salespeople will be much, much easier, and you can basically think the same thing about marketing, about your work with, with with setting up the interview with me, for example. There there's so much potential for automation if you they have this tiny steps and this planning ahead that you still can interact and change with and nothing happens with you approving what the AI plans. But this basically the midterm goal that we want to achieve, allow for this to to to be the glue between all these systems and use AI to actually have, like, end to end automations that take away, like, the burdensome annoying little steps we have to do by changing tools, changing platforms, duplicating data, and so


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:30:19]:

on. It also sounds to me like you would make the sales process more tractable as well as more efficient.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:30:28]:

Absolutely. Absolutely.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:30:32]:

Do you also see because you have sales on one side, do you also see, something like this you could offer to customers in terms of product development, product ideas that they would they they may like to have in the future?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:30:48]:

That's a that's a very interesting question. I if you if you think from, like, a product manager perspective, I think, having better access to user feedback by being able to search through it more proficiently, and also by being able to search the web compared with the competitors, and to to probably combine information from your CRM, from from your support, and so on to get a more holistic view of the customer actual needs can be very helpful. In addition, what what's also important, if you have tools that have analytics within your app, you want to combine these this information, like, how often was feature x used versus feature y? Can you group that into cohorts? We saw updates that currently are done manually that maybe not now, but in 6 months or so, AI could do for you. And, again, we see it ourselves as a platform enabling that. We are not a CRM. We are not a analytics tool, but we want to integrate or we are integrating with these tools to basically tie this information together, to give you, like, an assistant, like a like a student intern that can do meaningful work. It probably needs some oversight and some correction from time to time, but it helps you to do complex steps with a few instructions, and less amount of time spent than if you would have you if you would have done it yourself.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:32:30]:

Sounds pretty good. So so we already know about your future plans. We usually close out those interviews with 2. Now we do 3 questions. I would assume you are open to talk to new investors.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:32:45]:

Absolutely. So when we transition from the the project based rocket loop, work to to our product company. We did a very small friends and family round, and we are currently planning for a pre c round, c round. The pre c drawn probably going to close by the end of the year and the c drawn's somewhere next year. So so we are very much interested into discussions with the investors. We there's still some room for business angels, but start at the end of year the year, we will probably talk more to institutional investors.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:33:25]:

Sounds pretty good. Would you also like to hire more talented people? Do do do you offer jobs?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:33:33]:

Yes. If you Always. Yes. Mostly mostly in in communications, marketing, sales, and engineering. Mhmm.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:33:46]:

For everybody who would like to learn more, for the investors, we link down your LinkedIn profile, and we also link down here your career website. My last question since this is sponsored by HASSAN Trade and Invest and the European Enterprise Network, HASSAN, Is there something you would like to address to the decision makers here in the state what they are already doing good and or what they could improve in order to make this a more sustainable start up hop here?


Patrick Helmig | Co-Founder | CEO | Omnifact [00:34:21]:

The thing is the thing is, I there's Hestia and AI, and they do a pretty good job. I I think I think we have very strong hop in in Frankfurt when or it hasn't when it comes to, finance for the finance industry. We also have one with the pharma industry, but I have the impression that they are not so much involved with all the, startup AI and and data, meet ups and events and so on. So maybe that could be an improvement.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:34:58]:

What is interesting though, we have been in talks with public, entities, but not from HES HESIEN, from HESIEN yet. So, from what I know so far is HESI, HESIEN does a great job with with enabling startups. I hope to hopefully, the next time we speak, I can say more, about the the AI aspect of it because for now, we have not taken too much steps into finding that out. Mhmm.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:35:34]:

Sounds pretty good. After long weeks of trying to organize that and more than 35, minutes of recording time, Patrick, I wish you all the best. Best of luck and thank you very much.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:35:46]:

Thank you, Joe. It was a pleasure, and thank you for your time.


Jörn "Joe" Menninger | CEO and Founder Startuprad.io [00:35:51]:

Pleasure was all mine. Bye bye.


Patrick Helmig | Co-Founder | CEO | Omnifact [00:35:53]:

Bye bye.


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