Document intake and review
Read invoices, contracts or forms, extract the fields, check them against your records and route exceptions to a person.
Capability
AI agents that do real work, safely.
We design and build agents that use your tools, follow your rules and bring a person in when the stakes are high, so repetitive work gets done without losing control.
Overview
What this means for you.
An AI agent is software that can read a request, decide which steps are needed and carry them out across your systems: look up a record, draft a reply, update a ticket, file a document. Done well, it removes hours of copy-and-paste work from your team. Done badly, it is a demo that nobody trusts.
Our work sits on the trustworthy side of that line. Every agent we build has a clear job, a defined set of tools it may use, approval steps where they matter and a full record of what it did and why. We measure it against real examples before it goes live, and we keep measuring after.
Agents scoped to one clear job
We start from a single workflow with a measurable outcome, not a general-purpose assistant that tries to do everything.
Connected to the tools you use
Integrations with your CRM, help desk, ERP, databases and internal APIs, with only the permissions the agent needs.
People in the loop
Approval steps for sensitive actions, clear escalation paths and simple ways for your team to correct the agent.
Grounded in your data
Retrieval over your documents and records, so the agent answers from your sources instead of guessing.
Evaluated before launch
Test sets built from real cases, with quality, cost and speed tracked against agreed targets.
Audit trails by default
Every action, tool call and decision is logged, so you can review what happened and improve it.
Use cases
Where agents earn their keep
The best first agents take on work that is frequent, rule-based and currently done by hand.
Support triage and drafting
Classify incoming requests, pull the customer's history and draft a reply for an agent to approve or edit.
Operations follow-up
Chase missing information, update systems after a meeting or order, and flag anything that needs attention.
Internal research assistant
Gather information from several systems and summarize it into a brief your team can act on.
How we work
A clear, steady way of working.
Discover
We map the workflow, agree what success looks like and collect real examples to test against.
Design
We define the agent's tools, permissions, approval points and failure handling, then prove the approach with a working prototype.
Build
We integrate the agent with your systems in short iterations, with regular demos and an evaluation suite that grows with it.
Support
We launch with monitoring and logging in place, then tune prompts, tools and rules as real usage comes in.
FAQ
Common questions.
What is the difference between an AI agent and a chatbot?
A chatbot mainly answers questions. An agent can also take actions in your systems, such as updating a record or sending a draft for approval. Many projects combine both.
How do you stop an agent from doing something it shouldn't?
Agents only get the tools and permissions their job needs. Sensitive actions require human approval, outputs are checked against rules, and everything is logged for review.
Which AI models do you use?
We choose the model per task based on quality, cost, speed and your data requirements. We can work with the major model providers or models hosted in your own cloud.
How long does a first agent take?
A focused first agent usually reaches a working pilot in four to six weeks. Our AI Agent Pilot package is designed for exactly this.
Next step
Start the conversation
Have a workflow an agent could take on?
Tell us about it. We'll reply within one business day with an honest view of whether an agent is the right fit.