Most AI guesses, then sounds confident; ours is built to know, and to prove it
Four layers turn the latent information in your documents into knowledge-powered agents you can stake a deal on. If Agents is "show me," Platform is "prove it."
Agents → Platform → Capabilities
Yes, derated to 3.2 kW above 95°C ambient. Fit for sealed outdoor use with the DIN kit.
One pass of the engine: a document in, an answer you can stake a deal on out.
- 01 AI-ready extraction
- 02 Knowledge graphs
- 03 The harness
- 04 Explainable AI
One chain, four steps. Latent information in, knowledge-powered agents out, and every answer traces back to the source.
AI-ready extraction
Can it read my documents, tables, and drawings, warts and all?
Extraction is the foundation: if the engine cannot read the datasheet, nothing downstream matters. This is where the accuracy number is earned, so the benchmark lives right here.
Extraction accuracy, our benchmark
Knowledge graphs
Does it understand my products, or just retrieve matching text?
The extracted facts become a graph of your products and how they relate. That is why answers are precise and relational, not chunk-retrieval guesswork. This is the answer to the "isn’t this just RAG" question.
The harness
How does knowledge turn into work my team can use?
The harness moves the story from knowledge to action: it lets an agent take steps, call your systems of truth, and complete a task, which is what makes these agents and not a search box.
Explainable AI
Can I trust the answer, and see why?
Every answer traces back to its source, with the reasoning shown and citations inline. Explainability is the trust payoff of the whole pipeline, and the reason you can stake a deal on it.
The controls your security team will ask about
SOC 2 Type II
Audited controls, independently verified.
Your data stays yours
Grounded in your documentation, never used to train shared models.
Deploy where you work
Website, Slack, CRM, email, and more, stood up by our engineers.