Technology
Collections that index themselves. An agent harness with rails built into the frame. Experiences that compose from blocks. A governance fabric that wraps all of it — engineered end to end, documented here layer by layer.
Layer 1
Work arrives as documents, records and institutional knowledge. A collection is where it becomes computable: typed, indexed, lifecycle-managed.
PDFs, scans, spreadsheets, email. Classified on arrival, extracted with page-level citations, chunked and embedded into the vector index — searchable by meaning, not just keywords.
Records with schemas: entities, deals, assets, people. Schema inference on ingest, typed fields, and the same citation discipline — every value traces to its source.
Policies, SOPs, playbooks — auto-vector-indexed so agents ground their answers in your institution's own rules, with retrieval that cites the exact passage.
Every collection carries a lifecycle: ingest → classify → extract → index → monitor, defined as a workflow you can inspect and rerun — state is never a mystery.
Layer 2
An agent here is a harnessed worker: instructions, tools, memory and guardrails assembled in a frame that evaluation holds to account.
Guardrails live in the runtime: allowed tools, allowed data, policy checks on outputs, escalation the moment confidence drops. The tool surface itself is governed — 195+ built-in tools across 35 modules, exposed over MCP, allow-listed per agent.
A single agent for a task. Sub-agents for delegation. A crew when perspectives must check each other. An xflow when the pipeline must be deterministic and replayable. A mesh when it must scale: a pub/sub DAG with dynamic 1→N fan-out — one loan file or ten thousand, same topology, more workers.
Golden sets, scored runs, regression gates. Agents ship when they pass evals, and keep passing them in production — the same discipline you'd demand of code. Team runs capture every step, so a bad answer is a traceable answer.
Underneath
The unglamorous parts are the point: the platform is engineered to be boring at 2am.
Mesh workloads run on queue-backed workers — pub/sub topics decouple stages, so throughput is a worker count, not a rewrite. Fan out to the size of the book.
Xflows and mesh runs are captured end to end: inputs, outputs, retries per node. Re-run yesterday's pipeline and get yesterday's answer — or a diff you can explain.
Traces per agent step, run history per workflow, token and latency budgets with alerts. Live operations dashboards watch queues, indexes and workers — drift is a page, not a surprise.
SSO/SAML, role-based access down to collection and action, tenant isolation, encryption in transit and at rest. Least privilege is the default, not a hardening project.
Layer 3
Agent output becomes useful inside the way a team actually works. Surfaces assemble from blocks, so your process reaches your screen the day you shape it.
Drag a card — a spread, a summary, a checklist, a chart — onto a page. Cards bind to collections and agents; layout is yours, data stays governed.
A working surface per job to be done: the underwriting workspace, the claims workspace. Assembled, not custom-built.
Everything the UI can do, the API can do. REST endpoints, webhooks on lifecycle events, exports that leave whole — no data hostage-taking.
The fabric
Every layer above runs inside the same fabric — built for the people who answer to bank examiners, CISOs and general counsel.
Your policies encoded as runtime constraints. Exceptions surface and escalate — never silently pass.
Every agent action logged: which document, which value, which tool, which policy, which human. Built for the exam.
Approval checkpoints where you define them. Agents prepare; named people decide.
Traces, run history, token and latency metrics per agent and per workflow. When something drifts, you see it first.
Role-based access down to collection and action level. Least privilege as the default posture.
Your data, your indexes, your runs — isolated. Encryption in transit and at rest. SSO/SAML.
The demo can be a whiteboard session: your stack, your constraints, our engineers. Bring the hard questions.
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