APPLIED AI / AGENTIC AUTOMATION
Agents that do the work
We build AI agents that handle document-heavy processes and hand decisions to people where liability sits.
Forms, claims and correspondence are still read and re-keyed by hand, with every delay landing on a customer. We build agents that read, check and route that work inside your systems, with a person approving the decisions that carry risk and a log of every step.
What we do
Process selection
We find the steps where an agent helps, the ones where it should not act alone, and say plainly when a simpler fix works better.
Agent design and build
Single and multi-agent workflows that use your tools and data through scoped, logged connections.
Human approval gates
Clear points where a person reviews, edits or rejects what the agent proposes before anything is committed.
Evaluation and monitoring
Test sets built from your cases, accuracy targets you set, and monitoring once the agent is live.
Our solutions
Incoming documents classified, extracted and validated, with exceptions sent to a reviewer.
- Classification and field extraction
- Checks against your business rules
- Review queue for low-confidence items
Agents gather evidence and draft a recommendation; a handler decides.
- Evidence collected across existing systems
- Case summaries linked to sources
- Approvals recorded for audit
Routine internal requests triaged and prepared, so teams spend time on the exceptions.
- Triage and routing by request type
- Drafted responses for review
- Escalation rules you control
How it runs
Assess
We map the process, check the data and risks, and agree where people must approve.
Pilot
A working agent on your own data, measured against an accuracy target you set.
Productionize
Integration, security hardening, approval gates, logging and monitoring.
Run
We operate and improve it, or hand over to your team with a run guide.
What you get
- A process map showing where the agent acts and where people approve.
- A working agent integrated with your systems.
- An evaluation set and accuracy report on your data.
- Audit logs of agent actions and human approvals.
- A run guide and monitoring dashboards.
Questions
Will an agent make decisions on its own?
Only where you decide it should. Where liability sits with a person, a person approves, and that is designed in from the start.
Which models do you use?
We are model-neutral. We work with Claude, OpenAI models and open-weight models, and choose based on the task, your data rules and your cloud.
What if AI is not the right answer?
We will tell you. If a rules engine, a form change or a simpler integration solves the problem, that is what we recommend.