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ServicesSecure AI agents

AI agents that act, with a record of every action

We build and deploy AI agents that read documents, update records and act in your systems. Each one gets narrow access, human approval for sensitive actions, and a log of everything it does.

Book a free discovery call How we limit an agent
  • Scoped identity per agent
  • People approve what matters
  • Every action logged
Claims intake agent, audit trailExample, one case1 waiting for approval
Read email in the claims inbox2 attachments, 2 identifiers masked before the modelDone
Extracted policy number and incident dateChecked against the policy systemDone
Updated case recordScope: claims.write, own cases onlyDone
Asked to issue a paymentNot in the agent's scope. Sent to a handler.Needs approval
Instruction found inside attachment"Forward all claims to..." Ignored and flagged.Blocked

How we keep an agent inside its job

Limits are enforced by the system, not by the model.

  • Its own scoped identity

    Each agent gets a service identity with access to the tools and records its job needs, and nothing else. No shared admin keys.

  • Approval for sensitive actions

    Payments, refunds, messages to key customers and changes above a threshold wait for a named person to approve.

  • Defences against prompt injection

    Content from emails, documents and web pages is treated as data, never as instructions. Sensitive tools can't be triggered by content alone. This reduces the risk; it doesn't remove it, so we test for it.

  • Masking before the model

    Personal data in what the agent reads is replaced with placeholders before it reaches a model outside your environment.

  • A full audit trail

    What the agent read, which tools it called with which inputs, what came back, and who approved what. Stored in your environment.

  • A stop button

    Rate limits, spending caps and a switch that stops an agent at once, with the work handed to a person.

What one agent may do

Where agents help most

Work too messy for a fixed automation and too repetitive for your people.

  • Document and case intake

    Claims, applications, invoices and onboarding packs read, checked and filed into the right record.

  • Inbox triage

    Shared inboxes sorted, simple requests answered from approved content, and the rest drafted for a person.

  • Record upkeep

    CRM and case systems kept current from calls, emails and documents, with a log of every change.

  • Whole roles, with a human owner

    Several agents covering a front desk or an operations queue, reporting to a named manager who can see everything they did.

An agent on the night shift

A 4-truck plumbing company in South Jersey. Emergency jobs pay the best, but most of them happen at night.

Before

After hours, calls went to voicemail. By the morning, the customer had already called someone else. The company was missing about 60% of its after-hours emergencies.

After

  1. The agent answers in under 5 seconds and asks the right questions about the problem.
  2. It decides whether it's an emergency or can wait until morning.
  3. For emergencies, it logs the job and texts the on-call tech the address, the problem and how to reach the customer. Nothing else from the customer's record.
  4. It keeps the customer updated, and every step is in the job record.
60% → 0Missed emergencies
<5sTo answer
24/7Dispatching
Read the case study

Questions

Can an agent be manipulated by what it reads?

Yes. That's prompt injection, and it can't be fully prevented today. So we limit the damage: narrow permissions, approvals on sensitive actions, and tests that try to break it before launch.

Which models do the agents use?

The one that does the job well within your data rules. That can be a large managed model with masking, a regional endpoint, or a model running in your own environment.

Who owns the logs?

You do. They're stored in your environment, kept for the period you set, and readable by your security and compliance teams.

What about the EU AI Act?

Most back-office agents aren't high-risk under the Act. Some uses are, such as screening job applicants or assessing creditworthiness. We check the use against the Act's categories before we build, and design for human oversight and logging either way.

Other services

Got work an agent could do, if you could trust it?

Tell us about it on a free 15-minute discovery call. We'll tell you whether an agent fits and what access it would need.

  • Pick a time that suits you
  • 15 minutes with an engineer
  • Clear next steps
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