AI agents that run your repetitive decisions end-to-end
Repetitive decisions at scale do not need a person. We build agents that handle invoice processing, lead routing, compliance checks and follow-ups end-to-end, connected to your systems through open standards, logging every action, and escalating only the exceptions.
Automate a workflowWho it's for
Operations-heavy teams losing skilled people's time to repetitive, rules-based decisions: finance, sales operations, compliance and customer operations.
What we deliver
Agents that own a whole workflow, built on the safety controls that make them fit for production.
End-to-end agents
Agents that complete a whole workflow (read, decide, act), not just draft a suggestion for someone else to execute.
MCP integration
Agents connect to your enterprise systems through the Model Context Protocol, the open standard for secure, governed agent access. No brittle custom glue.
Immutable action logging
Every action an agent takes is logged and cannot be altered by the agent, so you have a complete, auditable record of what was done and why.
Exception escalation
Agents handle the routine and escalate only what genuinely needs human judgment, with the full context attached.
Safe-by-design infrastructure
Scoped credentials, approval gates on irreversible actions and per-credential blast-radius limits: the controls that make agents safe to run in production.
Human-in-the-loop control
You decide which decisions agents own outright and which require sign-off, and can move that boundary as trust grows.
How it works
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Find the right decisions
We identify the repetitive, high-volume decisions where automation pays off and the risk is well understood.
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Design the guardrails
Before any agent touches production, we design the scoped credentials, approval gates and audit logging that keep it safe.
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Build and connect
We build the agent and connect it to your systems via MCP, with the human-in-the-loop boundary you choose.
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Pilot on real work
We run the agent alongside your team on real cases, measure accuracy and escalation rates, and tune.
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Scale and operate
Once it earns trust we widen its scope and hand over an observable, maintainable system.
Proof
Down from 3 to 5 days. Manual processes replaced by automated pipelines and agents.
Automation collapses the time from a decision being needed to a decision being made, from days of manual handling to under a minute.
Questions we get asked
What is MCP and why does it matter?
The Model Context Protocol is an open standard for connecting AI agents to enterprise systems securely and with governance. Building on it means your integrations are portable and auditable rather than locked to one vendor's proprietary connectors.
How do you stop an agent from doing damage?
Layered controls: each agent gets credentials scoped to just its task, irreversible actions require out-of-band human approval, every action is logged immutably, and per-credential blast-radius limits cap what can go wrong. We treat agent safety as an engineering problem, not a policy document.
Which processes are a good fit?
High-volume, rules-based decisions where the logic is well understood: invoice processing, lead routing, compliance checks, data entry and follow-ups. Judgment-heavy or one-off work stays with people.
Do agents replace our staff?
They remove the repetitive load so your people spend time on the exceptions and the work that needs judgment. The agent escalates anything outside its remit with full context.
What if the agent gets something wrong?
It escalates uncertain cases rather than guessing, every action is auditable, and blast-radius limits contain any single mistake. You set how much autonomy each agent has.
Related
Have a repetitive process that's eating your team's time?
Let's scope an agent