Stéphan Donzé is the founder and CEO of AODocs, a cloud-native document management platform that transforms enterprise content into actionable intelligence. Unlike legacy systems limited to basic storage, AODocs combines robust document control with workflow automation, enabling businesses to streamline complex processes across industries.
From sales proposals and claims management to engineering and manufacturing, AODocs uses generative AI to extract structured data from unstructured documents—at scale.
What inspired you to start out AODocs in 2012? Was there a selected problem you saw in document management that wasn’t being addressed on the time?
It got here from the concept of bringing Business-to-Consumer (B2C) technologies, pioneered by Google, to the enterprise. This included cloud-based, serverless, and routinely scaling technologies that were absent in enterprise software on the time.
On the time, Google was advocating for applications to adapt to the cloud by moving away from thick clients and embracing browser-based and serverless architectures. Unlike Microsoft and Amazon on the time, Google’s stance was that cloud applications should adopt a really different architecture than on premise software. I saw a chance to create something latest by combining old and latest approaches.
Early adopters of cloud technologies in enterprises, who had adopted Gmail and Google Drive, wanted to increase these advantages beyond email and collaboration to business-critical documents. There was an absence of solutions available in the market to fulfill this need, as traditional document management systems were on-premise with old software and architectures. This gap presented a chance to construct something latest from scratch on the precise cloud architecture, working with these early adopters.
Many enterprise SaaS corporations struggle with customer adoption. How did you persuade major enterprises like Google or Veolia to trust AODocs early on?
Allowing customers to maintain documents of their own cloud storage was a major consider convincing enterprises. AODocs manages documents, including sharing permissions and business processes, however the documents remain inside the customer’s environment (initially Google Drive, later Azure, Google Cloud Storage, and Amazon S3). This fundamental characteristic reduced the perceived risk for patrons, and made them more comfortable working with a small and young company.
One other key reason was close customer relationships. We co-built and co-developed with customers, especially within the early stages. This proximity and reactivity in fixing problems and making improvements built trust and further reduced the perception of risk.
This was ultimately what convinced corporations like Google, Veolia, Ascension, Pinnacol Assurance and others to adopt us.
Looking back at your 13+ years leading AODocs, what were among the most crucial decisions that led to the corporate’s success?
The choice to maintain customer documents in their very own cloud storage is an enormous consider our success and stays a key differentiating factor.
Developing the product by staying very near customers was also critical. Every thing we construct is inspired by or validated through customer needs. We avoid constructing features with out a clear customer use case.
Our ability to sort through customer requests to discover common and replicable needs that profit the whole customer base, versus very specific individual requests higher addressed by skilled services, is something we have been good at.
AODocs was born within the cloud and has now evolved into an AI-powered solution. What were among the biggest challenges in making that transition?
It isn’t a lot a transition but a continuity. Being born within the cloud inherently made AODocs easy to integrate with latest, cloud-based technologies, including AI.
AI models like ChatGPT and Google Gemini are cloud-based, making it natural for AODocs to interface with them and add AI capabilities to our document processing platform.
We view AODocs as a “spine” or an “assembly line” for document processes, where AI is solely a brand new “limb” or “module” that may be plugged in to boost the platform. We didn’t foresee the particular emergence of AI in 2022, but our cloud-native architecture was designed for extensibility and integration, making the adoption of AI a natural step.
How does AODocs balance automation with human oversight, ensuring compliance and accuracy without removing human validation?
We offer the tools to customers to make use of AI at various steps of their document processes. The choice of how much autonomy to present AI is ultimately made by the shoppers on a case-by-case basis.
Customers can configure their processes for full automation, full human review, or a mixture of each at any AI step. We recommend identifying easy cases suitable for full AI automation (e.g., detecting missing documents in a request), while for complex cases, AI may be used to hurry up the human review, typically by generating summaries of complex documents.
Essentially, we give customers 100% control over the extent of human oversight of their processes by providing the configuration tools.
AODocs is shifting its platform to give attention to AI agents for document processing. What drove this decision, and the way do AI agents improve upon traditional document management systems?
AI agents are a brand new capability that may be integrated into our existing “assembly line” for documents.
The first driver for our excitement about AI agents is their potential to bring significant speed to specific tasks. For easy tasks like rejecting incomplete documents or routinely accepting low value, straightforward claims, AI can enable full automation.
For complex tasks, AI agents can dramatically speed up processing by summarizing long documents, allowing humans to review key information much faster. AI excels at ingesting large amounts of data and providing concise summaries, saving human reviewers significant time. This increased speed and efficiency enhance the worth of the AODocs platform.
Enterprise search stays a serious challenge, with corporations struggling to retrieve relevant documents. How does AODocs’ AI-powered solution tackle discoverability issues higher than existing enterprise search tools?
AI chatbots represent a serious improvement over traditional enterprise search by allowing users to ask questions in natural language and receive straightforward answers. Nonetheless, they’ve a major flaw: they can’t distinguish between valid, up-to-date documents and drafts, incomplete, or obsolete files.
We address this challenge by ensuring AI agents use only the precise information to supply answers. Traditional search presents users with a listing of potential matches, allowing them to discover probably the most relevant document (equivalent to distinguishing between a signed contract and a draft).
In contrast, AI chatbots offer confident answers but hide the underlying search process. This creates an increased risk of using outdated or misinformation, as users don’t have any visibility into which documents the chatbot used to formulate its response.
Our role is to curate and guarantee that every one documents within the knowledge base have been properly validated and are up-to-date. This makes them secure for AI agents to make use of as information sources. By ensuring AI-powered search relies only on trusted and controlled information, we significantly reduce the chance of inaccurate responses.
With generative AI becoming a key a part of document processing, what specific AI technologies or models does AODocs leverage to enhance accuracy and reduce manual work?
LLM models excel at transforming existing content, equivalent to summarizing complex documents, translating text, and categorizing files. These tasks have a really low risk of hallucinations, which is why our AI usage strategically focuses on these activities.
AODocs primarily leverages AI for rephrasing, repurposing, and remodeling existing text quite than creating latest content. When working with the precise material, generating summaries, translating documents, and categorizing content all maintain a low probability of error. Similarly, our data extraction capabilities—identifying due dates or key information from documents—remain grounded in existing content to attenuate inaccuracies or “hallucinations.”
By accelerating information ingestion and supporting human reviewers, these AI capabilities often improve efficiency by a major factor. This creates tangible value while fastidiously avoiding the risks related to AI-generated content created from scratch.
There’s an extra advantage. AODocs integrates seamlessly with any LLM, giving our customers freedom to decide on their preferred provider. This versatile architecture also ensures we will quickly incorporate future models as they turn into available, positioning our customers to learn from the inevitable AI innovations emerging within the months and years ahead.
Certainly one of the largest AI challenges in document processing is hallucinations or inaccurate responses. How does AODocs make sure that AI-generated insights are trustworthy and reliable?
The important thing to making sure trustworthiness and reliability is grounding. We make sure that AI is used to rephrase or transform information from trusted sources.
In document processing, AI is asked to summarize or translate existing documents, minimizing the prospect of hallucination. In AI chatbots or agents, the system is supplied with extracts of controlled documents and is instructed to generate answers only from those extracts—the LLM must at all times quote the sources from which it generated its answer—without using general world knowledge or external information. This prevents AI from inventing or providing information not explicitly present within the validated documents.
With AI transforming enterprise software, where do you see AODocs in the following five years? What role will AI agents play in the long run of document management?
Our core business as a document management platform won’t change. Our mission stays to make sure the trustworthiness, currency, proper business process adherence, and traceability of managed information.
AI is each a brand new need for controlled information (to feed trustworthy data to AI chatbots) and an accelerator of business processes involving documents. AI can speed up tasks like summarizing, translating, and categorizing documents, making human users more productive.
In the following five years, we aim to supply the tools for corporations to simply apply AI where it is sensible to boost their business processes. AI agents will play a vital role by amplifying and accelerating our core missions: providing trustworthy information, ensuring using the proper document versions, helping avoid human errors, and facilitating access to business processes. We would like to assist corporations use AI effectively and strategically to spice up productivity.
