Gnostic.
Documents, messages, the knowledge in people's heads — Gnostic connects it all into one living knowledge graph that empowers your teams and AI agents. The result: lower operational costs, less risk, and higher productivity.
Hundreds of live shipments, each trailing a stack of paperwork. Know what's complete on every deal at a glance.
Exposure per counterparty and documentation gaps across every active deal — surfaced before the audit finds them.
Drowning in manual document checks, answerable to a regulator. Every answer has to carry its evidence.
Board pressure to "do AI" — and a policy that forbids sending data to public models. Both, satisfied at once.
“The answer is always somewhere in the documents. Finding it is somebody's entire job.”
— what we hear in every first conversation with a document-heavy team
Specialists reopen the same files to pull the same facts, operation after operation, deal after deal. The knowledge evaporates the moment the file closes.
Same counterparty, same deal — scattered across drives, email, and systems. Every link is rebuilt from scratch, every time.
Your data would leave your jurisdiction, with no audit trail and costs that climb per question. Compliance is right to say no.
Every party, contract, shipment and payment, extracted and linked — and kept current as new files arrive.
Every answer traces to its source documents. Structured facts, not generated guesses.
Compliance sees gaps. Operations sees deadlines. Financing sees exposure. One graph, many views.
Missing certificates, approaching payment dates — surfaced automatically, not at audit.
It starts from a pre-built domain ontology — your document types, entities and relationships, modelled before a single file is read. Four stages run on top of it.
Drives, email, systems — every new or changed document is noticed the moment it lands.
Each document is classified and its facts pulled into structure — against your domain, not a generic template.
Facts become a graph: parties, contracts, shipments and payments, linked. This is the knowledge — built once, kept live.
Questions read the graph directly. Nothing is reprocessed, so the next answer is effectively free.
Answers come from a structured graph, queried directly. Nothing to hallucinate.
We model your domain first. Extraction follows the ontology — not keyword similarity.
Nothing leaves your perimeter. Local models supported end-to-end, air-gap included.
We don't move or replace your files. We connect what's inside them, wherever they live.
We're building Gnostic with a launch partner — a major commodity trading house, in one of the most document-heavy corners of finance. The domain came first: every document type and relationship modelled before a line of pipeline code.
Why start here? Because if it works in one of the most document-heavy corners of business, it works anywhere knowledge is buried in documents and people's heads.
Which trades with Meridian SA are still missing a certificate of origin?
Which shipments arrive next week with incomplete documentation?
What's our total exposure to counterparty Aurelius across active deals?
✦ Illustrative queries from the trade-finance pilot. Every answer is traceable to its source documents.
We map the territory with your specialists — document types, entities, relationships. The ontology is the output, and it's yours to keep.
A real corpus from your archive, ingested into your environment. Your team asks real questions and checks the sources.
Live document flow connected, role views configured, your IT in control. Cloud, private, or fully air-gapped.
During modelling we need a few hours a week from two or three of your specialists. We do the rest.
Agidel implements AI for financial institutions — same discipline as the product: model the domain first, stay inside your perimeter, keep every output auditable.
Where AI genuinely pays off — and where it doesn't. Honest scoping and an architecture that fits your compliance posture.
Document processing, knowledge extraction and workflow automation — on your data, your infrastructure.
Private-cloud and on-premise AI, air-gap included. We run it, or hand it to your team.
And sometimes we're not the fit. Want a general-purpose chatbot for everyone? A copilot licence is cheaper. Data already in one clean database? Just query it. Either way, we'll tell you on the first call — and point you to who can.
Most teams run Gnostic as a managed service in our secure cloud — the fastest way to get value, with Swiss data centres available. If your compliance needs more, we can deploy inside your own cloud account, on your servers, or in a fully air-gapped environment where nothing leaves your perimeter. The right model for you is settled in the architecture phase.
The pipeline is model-agnostic. In connected environments it can use the frontier model of your choice under your agreements; in private and air-gapped deployments it runs on local models end-to-end. Model choice is part of the architecture phase.
Every answer is a query against structured data, and every extracted field links back to the document it came from. Your team verifies against sources during the pilot — that verification step is built into the engagement, not skipped past.
The approach — ontology first, then extraction, then the graph — is domain-independent. Trade finance is where the pre-built ontology exists today; for adjacent domains like project finance, syndicated lending, or structured products, modelling your domain is the first phase of the engagement.
Pricing follows document volume ingested, not questions asked — so the cost is fixed and plannable, and no one has to ration their curiosity. Design partners get preferential terms; exact numbers depend on corpus size and deployment, which we'll size up on a first call.
Both, but always toward something running. Agidel is an engineering team — backgrounds in finance, production AI systems, planet-scale infrastructure, and AI security. Advisory exists to scope the build, not to replace it.
Start with a focused pilot — a slice of your real corpus, ingested inside your environment, your team asking real questions and checking the sources. A few hours a week from your specialists is all it takes to begin, and early teams get preferential terms and an ontology tuned to their business.
A founder reads every message. You'll hear back within 48 hours.