Enterprise AI agents that can show their work.
Most enterprise AI doesn't fail at the demo. It fails at review — when someone asks how the system reached its answer and nobody can say. We build agents on deterministic cores, with the evaluation evidence to get them past that conversation.
The gap isn't capability. It's evidence.
The Pilot Works
A demo runs, the output looks right, and everyone in the room is convinced.
Review Begins
Risk, compliance, or audit asks how the system reached its answer, how often it's wrong, and what happens when it is.
Project Stalls
Not cancelled — just parked, indefinitely, in the gap between a working prototype and something anyone will sign off on.
The model doesn't make the decision.
In our agents, the logic that matters runs on deterministic rules, not model inference. Calculations are computed, not generated. Thresholds are enforced in code, outside the model. Where a language model is used, it orders and phrases results — it has no access to tools and cannot execute actions on its own.
That constraint is the point. It means the same inputs produce the same outputs every time, every result traces back to the rule that produced it, and the failure modes are ones your team can reason about.
Every agent ships with the evidence that it works.
We evaluate agent performance, reliability, and risk before deployment and continuously after it — groundedness, factuality, task completion, safety, latency, and cost. You get the harness and the results, not just the agent.
If an agent's accuracy drifts after a model update, you find out from a regression test rather than from a customer.
What we build
Enterprise AI Agents
AI agents designed to interpret goals, retrieve context, use approved tools, coordinate tasks, and involve people when judgment, review, or authorization is required.
Enterprise Knowledge Assistants
Secure, grounded assistants that help employees access trusted verified organizational knowledge through conversational and search-based experiences.
Intelligent Document Processing
Automated extraction, classification, validation, summarization, comparison, and routing of complex documents.
AI Workflow Automation
Multi-step workflows combining AI agents, enterprise applications, APIs, business rules, and human decisions.
What it runs on
Data Quality & Governance
Profiling, validation, schema monitoring, anomaly detection, and governance reporting for enterprise data.
Research & Business Intelligence
AI systems that collect information from approved sources, synthesize findings, and preserve evidence.
Industries
Targeted compliance-heavy and knowledge-intensive sectors:
Financial Services
Reconciliation, invoice and PO matching, and compliance documentation — back-office workflows where the value is countable and the audit trail is mandatory.
Healthcare & Life Sciences
Prior authorization, claims documentation, and policy retrieval — administrative workflows, with clinical decisions left to clinicians.
Technology & Professional Services
Internal support, knowledge retrieval, and document workflows — grounded in your own documentation, with citations on every answer.
Find out where your AI project would stall.
Answer 5 quick questions about your workflow, data, and approval processes. Get a custom brief identifying potential failure points and necessary review evidence.
It takes about 5 minutes and there's no call attached to it.
Working on something specific?
We run a two-week Agent Readiness Assessment: we sit inside one of your workflows, map where an agent would fit, and hand back a build specification with the evaluation criteria attached. Fixed fee. You own the output whether or not we build it.
We're running the first two at no cost.