Document Intelligence - Dodocs.ai Transforming Document Workflows with AI: Dan Gudkov
In a world where businesses generate mountains of documentation but still rely heavily on manual processes, Dodocs.ai stands at the intersection of AI innovation and real-world operational efficiency. At its core is Dan Gudkov, an entrepreneur with a sharp eye for inefficiencies and a passion for building practical, scalable solutions. With experience ranging from tech startups to running a restaurant, Dan has seen firsthand how businesses—large and small—struggle with document workflows. This insight became the seed for Dodocs.ai, an AI-driven platform that automates and intelligently processes enterprise documents using a unique multi-microservice architecture and multiple open-source LLMs.
Dodocs.ai is an enterprise-grade SaaS platform focused on AI-powered document automation. With a foundation built on microservice architecture and open-source large language models (LLMs), Dodocs.ai transforms how companies manage, extract and utilize data from documents across diverse industries. From invoice processing to ERP integrations, the platform provides a robust, scalable and intelligent solution to reduce manual effort, increase accuracy and create value in operations where documentation plays a crucial role. Dodocs.ai is at the forefront of what its founder calls “Tech Revolution 5.0” where AI becomes the cognitive layer behind enterprise workflows.
TFS: Hi Dan, thank you so much for taking the time to speak with us today. It’s great to have you here!
Dan Gudkov: Thank you! I’m really glad to be part of this conversation. It’s always a pleasure to share what we’re building with Dodocs.ai and to talk about the real impact AI can have when it’s implemented thoughtfully.
TFS: Absolutely—and there’s so much to dive into. Let’s start from the beginning. What inspired you to create Dodocs.ai and what gap in the market were you aiming to fill?
Dan Gudkov: The inspiration for Dodocs.ai came from years of grappling with documentation inefficiencies in multiple industries. I’ve been involved in both tech-heavy environments and traditional businesses like the restaurant I used to run. Across these varied experiences, I consistently noticed that teams were overwhelmed by documentation tasks—whether it was procurement paperwork, inventory sheets or financial reports. These were manual, repetitive and error-prone processes that drained time and resources.
I realized that while data was being generated and stored, it was rarely used effectively because the access layer—the document workflows—was broken or archaic. That’s where Dodocs.ai was born. I wanted to build a tool that could not only automate but intelligently manage documents by using AI to interpret, extract and process information seamlessly across industries. The goal wasn’t just efficiency—it was about empowering companies to truly harness the value hidden inside their documents.
TFS: The concept of AI-driven document automation has been explored by various platforms. What makesDodocs.ai truly unique?
Dan Gudkov: You’re right—document automation isn’t a new concept. What makes Dodocs.ai stand out is our architectural philosophy and our hyper-focus on real-world applicability. We designed Dodocs.ai using a multi-microservice infrastructure that allows us to deploy different open-source LLMs for different types of tasks. This enables us to be much more flexible and scalable than traditional monolithic systems.
Moreover, we’ve zeroed in on operations that are universal across verticals—like invoice processing, logistics documentation and POS-related data flows. These are processes that occur in almost every business, regardless of the industry and we’ve designed our tools to be exceptional at automating those workflows with minimal customization. That gives us a strategic advantage—we’re not trying to be everything to everyone. We aim to dominate in very specific, high-volume use cases and be the best at it.
TFS: How do you see the role of AI evolving in legal and enterprise documentation over the next five years?
Dan Gudkov: In the next five years, I believe AI will become an inseparable layer of enterprise software, especially in documentation-heavy departments like legal, finance and compliance. Most of the friction in document workflows comes from manual interpretation and data entry—two areas where AI is already showing incredible results.
At Dodocs.ai, we’re focusing on what we call the “grey zones”—the spaces between existing automation systems where documents still need human intervention. For instance, a manager might spend hours reading contracts or transferring invoice data from PDFs into ERP systems. Our system already reduces that burden by up to 97% for specific tasks like data entry from original documents. This is just the beginning. We envision AI enabling a fully interconnected document ecosystem—where every document is automatically understood, categorized and acted upon by intelligent systems, allowing humans to focus on strategic decision-making.
TFS: Dodocs.ai integrates large language models (LLMs) to process and draft documents. Can you share insights into the training process and how you ensure accuracy?
Dan Gudkov: We use a robust system involving four open-source LLMs, each running in parallel within a modular architecture that we’ve built in-house. This approach allows us to compare, validate and cross-reference outputs in real-time. One model might be better at interpreting legal clauses, while another excels at formatting financial tables. By running them together and analysing discrepancies, we can achieve higher accuracy and reliability.
Beyond that, we’ve built a self-improving document catalogue system that grows more intelligent every day. Thousands of documents flow through our system regularly and this exposure helps refine our models through continuous learning and pattern recognition. It’s like a neural network that gains experience just as a human would—learning what to expect, how to interpret context and how to structure output more efficiently over time.
TFS: AI-generated documents often raise concerns about reliability. How does Dodocs.ai balance automation with human oversight?
Dan Gudkov: We understand that trust is everything when it comes to automation, especially in enterprise environments. That’s why Dodocs.ai is built with configurable human-in-the-loop systems. Organizations can set checkpoints, approval flows and customizable review protocols before any AI-generated data is accepted into critical systems.
This flexibility ensures our users can maintain control without sacrificing efficiency. Supervisors can verify data, choose export formats or decide whether the output gets pushed directly into their ERP, CRM or document management systems. It’s about enhancing human expertise, not replacing it. By shifting tedious tasks to AI and allowing humans to make final decisions, we create an ideal partnership between automation and accountability.
Q6. With capabilities like video call transcription and chatbot automation, what are the most challenging technical problems you’ve had to solve?
Dan Gudkov: One of the biggest challenges we’ve faced is handling unstructured and poor-quality data. For example, documents that are handwritten, scanned with smudges or partially erased are extremely difficult to process accurately. Traditional OCR (Optical Character Recognition) tools often fail or return unreliable results in such cases. We had to build custom preprocessing pipelines that include noise reduction, smart segmentation and handwriting analysis powered by AI to extract meaningful data from even the most compromised inputs.
Another major challenge was integrating Dodocs.ai into the wide variety of ERP, POS and inventory systems used by different clients. Each system has its own API structure, security protocols and data formats. We overcame this by designing modular APIs and adaptive connectors that allow seamless integration, regardless of the backend infrastructure. Our approach was to build once and scale infinitely—so even if the systems are radically different, Dodocs.ai adapts without requiring bespoke development for every client.
TFS: Dodocs.ai positions itself as a key tool for enterprises. How do you tailor your solutions to different industries with varying documentation needs?
Dan Gudkov: The key is in recognizing that while the industries may differ, the core document operations are surprisingly similar. Whether you’re dealing with an invoice in logistics or a procurement order in hospitality, the sub-processes—like data extraction, validation and archival—are mechanically the same.
We’ve spent a lot of time identifying these common denominators and building standardized modules around them. That’s why we created modular APIs instead of static workflows. This architecture allows clients to plug our automation directly into their environment and use it as part of a larger process. There’s no need to completely revamp how they work—we simply enhance what they already do. As a result, Dodocs.ai can be quickly deployed across various industries like finance, retail, legal and manufacturing with minimal friction.
TFS: What has been the biggest challenge in scaling Dodocs.ai and how have you overcome it?
Dan Gudkov: Our biggest challenge was focus. AI has so many use cases that it’s tempting to try and solve everything at once. Early on, we had multiple directions we could have pursued—from HR document automation to legal contract analysis to customer support transcription. But scaling a startup requires clarity and prioritization.
We chose to concentrate on procurement and bookkeeping automation, specifically because these are document-heavy processes with immediate ROI for clients. Once we validated the demand through client feedback and industry competitions, we doubled down on perfecting these workflows. That decision allowed us to create a repeatable, scalable product with a clear value proposition and it gave us a competitive edge.
TFS: As an AI-driven enterprise SaaS solution, do you see partnerships with law firms, financial institutions or government entities as part of your growth strategy?
Dan Gudkov: Absolutely. In fact, we’ve already begun forming partnerships in these areas. For instance, one of our enterprise clients is a large archival management company and we’re currently integrating Dodocs.ai into their accounting and Point-of-Sale software. These collaborations help us expand our use cases and improve our technology through real-world exposure.
Our long-term vision includes deeper collaborations with law firms, banks and government institutions. These sectors are highly document-intensive and often operate under strict compliance rules, which makes them ideal candidates for the type of reliable, secure automation we offer. Our APIs are enterprise-ready, which means we can plug into these high-stakes environments without compromising performance or data integrity.
TFS: AI in legal and enterprise applications raises concerns about data privacy and compliance. How does Dodocs.ai ensure security and ethical AI use?
Dan Gudkov: Security is non-negotiable for us. We’ve designed Dodocs.ai from the ground up to meet enterprise-level data privacy standards. For example, we use Microsoft Azure’s secure infrastructure to ensure that all data is encrypted in transit and at rest. We also support on-premise deployment options for clients with especially stringent compliance needs.
As for ethics, we mitigate bias and hallucinations by using a diverse set of LLMs, which are continuously evaluated and fine-tuned. We also provide clients with the ability to override or review AI decisions before they impact operations. Transparency, control and accountability are at the heart of everything we build. We believe that AI should augment human decision-making, not replace it blindly.
TFS: The automation of documentation could replace some human roles. How do you see Dodocs.ai complementing rather than replacing human expertise?
Dan Gudkov: This is a critical question. Our goal is not to replace humans but to liberate them from low-value, repetitive tasks. Right now, a large portion of skilled professionals’ time is wasted on mundane work like copying data from PDFs into spreadsheets. Dodocs.ai takes care of those tasks so that humans can focus on what they’re best at—critical thinking, creativity and strategic decision-making.
As AI tools become more advanced, we’re going to see a shift in job roles. Document managers might become AI supervisors or data quality analysts. The human role evolves, but it doesn’t disappear. In fact, those who embrace AI will become even more valuable because they can use these tools to amplify their impact. I think we’re headed toward a world where human expertise and AI work in tandem to deliver unprecedented efficiency and insight.
TFS: What measures does Dodocs.ai take to prevent AI hallucinations or biases from affecting critical business documents?
Dan Gudkov: We take a layered approach. First, we avoid relying on a single LLM. Instead, we use multiple open-source models that run in parallel, which allows us to compare outputs and flag anomalies. This system gives us a consensus mechanism, which dramatically reduces hallucinations and ensures that outputs are grounded in factual data.
Second, we apply task-specific tuning. We don’t let models run free; we guide them with strict context and defined scopes. And third, we maintain an active evaluation loop. Every new document processed adds to our training corpus and every client feedback point informs how we refine model behavior. Our ultimate goal is reliability—making sure the AI behaves predictably and correctly every time.
TFS: You mentioned the ambition to lead the Technological Revolution 5.0. What does that look like and where does Dodocs.ai fit into it?
Dan Gudkov: Tech Revolution 5.0, as we see it, is about intelligent infrastructure. AI won’t just be a feature; it will be a fundamental layer of every business process. Think of it like electricity—you don’t see it, but every modern tool depends on it. Similarly, AI will become the invisible force behind decision-making, execution and workflow automation.
Dodocs.ai fits into this future as the cognitive infrastructure layer for document-based operations. Our APIs, SDKs and microservices are designed to embed directly into other software platforms, effectively turning any system into an intelligent, self-operating engine. We’re not building a front-facing product—we’re building the foundation for smarter enterprise ecosystems.
TFS: Looking ahead, do you envision Dodocs.ai expanding into multilingual, jurisdiction-specific legal AI models?
Dan Gudkov: Yes, that’s definitely on our roadmap. We already support multiple languages, but the primary focus has been on English because that’s where most of our initial clients operate. However, as we expand globally, we’re developing jurisdiction-specific models that can handle local regulatory nuances and linguistic differences.
This is particularly important in the legal domain, where language precision is critical. Our ambition is to make Dodocs.aiadaptable not just to the industry but to the geography. Imagine a legal document in France being understood, processed and filed just as efficiently as one in the U.S—that’s the kind of global intelligence layer we’re working toward.
TFS: If you could change one thing about how businesses currently handle documentation, what would it be and why?
Dan Gudkov: I would change the fragmented, siloed and overwhelmingly manual nature of documentation workflows. Right now, documentation is scattered across departments, handled inconsistently and rarely used to its full potential. It’s treated as an administrative burden instead of a strategic asset.
My vision is a world where documents flow through AI-powered pipelines automatically—where data is instantly extracted, verified and connected to broader systems like CRMs, ERPs or BI tools. This would eliminate human error, reduce processing times from hours to seconds and unlock insights that were previously hidden in piles of paperwork. That’s the transformation we’re enabling at Dodocs.ai—turning documentation from a pain point into a competitive advantage.
TFS: Dan, this has been a truly enlightening conversation. Your vision for Dodocs.ai and its role in reshaping how businesses manage documents is incredibly forward-thinking. Before we wrap up, is there anything you’d like to leave our readers with—perhaps a message for aspiring founders or enterprises still hesitating to adopt AI?
Dan Gudkov: Thank you. It’s been a pleasure sharing our journey and vision. If there’s one thing I’d say to both founders and enterprises, it’s this: don’t wait for the perfect time to adopt AI—because that time is now. The technology is no longer futuristic; it’s ready, practical and already creating massive efficiency gains for those willing to experiment and evolve.
For founders, remember that innovation is about solving real problems, not chasing trends. We didn’t build Dodocs.aibecause AI was trending—we built it because managing documents was painful and wasteful. Start there, find the pain and use technology as your tool to solve it.
And for enterprises—AI is not here to replace your people. It’s here to elevate them. The sooner we shift from fear to curiosity, the more value we can unlock across every corner of an organization.
TFS: That’s a powerful message to end on. Dan, thank you once again for your time and for offering such deep insights. We’re excited to see how Dodocs.ai continues to push the boundaries of intelligent document automation and plays its part in shaping Tech Revolution 5.0.
Dan Gudkov: Thank you—it’s been an absolute pleasure. Looking forward to what the future holds!