The Agent Layer

Your systems stay. A layer of agents does the work between them.

The Agent Layer is how we build: agents with their own limited logins, your rules written down and enforced, a person in the loop wherever you want one, and a record of everything they do.

An AI agent working across connected business systems

Where the agents sit

The Agent Layer sits between your team and your systemsYOUR TEAMSalesCustomer ServicePurchasingFinanceOwnerTHE AGENT LAYERObserveSuggestAct with approvalLogYOUR SYSTEMSERPAccountingCommerceEmail & EDISpreadsheets

Your team

Decides, approves the exceptions, handles the relationships. The judgement stays with your people.

The Agent Layer

Reads documents and messages, applies your rules, acts in your systems, asks when it is unsure, and logs everything it does.

Your systems

Stay the record. ERP, accounting, commerce, your CRM, EDI, spreadsheets — nothing is replaced.

How an agent earns its keep

  1. Watch

    The agent sees the real work: inboxes, documents, the orders and bills your team handles. It does not act.

  2. Draft

    It drafts what it would do. Your team keeps working normally and compares.

  3. Approve

    Your team approves, edits or rejects each draft. Every correction teaches it your rules.

  4. Act with limits

    On the kinds of work it gets right, you let it act. Anything above your limits still comes to a person.

  5. Report

    You see what it did, what it escalated and why — every day.

Autonomy is granted per type of work, never all at once. You can move any agent back a stage at any time.

What you control

Set by you, changed any time
Approval limitsDollar amounts, new customers, price changes. Above your line, it goes to a person.
System accessWhich systems each agent can touch, and whether it can write or only read.
Working hours and send limitsWhen an agent runs, and how much it is allowed to send out.
Who gets the escalationsWhich person sees which exception, and where it lands.
Switching an agent offOne switch per agent. The work goes back to your team as it was.

The second agent is faster than the first

Every agent shares the same connections to your systems, the same map of your customers, items and part numbers, and the same rules.

Build Order Entry first and Customer Service already knows your orders. Build AR next and it already knows what shipped and what was disputed.

  • Order Entry Agent
  • Customer Service Agent
  • AR & AP Agent

One shared base

  • Connections
  • Customer & item map
  • Your rules
  • Action log

Agents vs. what you’ve tried

We still use rule-based automation where it's the right tool. Agents are for the work in between.
Rule-based automation (RPA, Zapier)Chatbots & copilotsAgents on The Agent Layer
Handles messy inputs (PDFs, free text)Breaks when the format changesReads them, but can't act in your ERPReads them and acts, inside your rules
Takes action in your systemsYes, on fixed pathsRarelyYes, with its own scoped login
Knows your customers and rulesOnly what's hard-codedOnly what's in the promptLearns and keeps them; corrections stick
Asks a person when unsureNo — it fails or does the wrong thingDepends on the user noticingBuilt in, with limits you set
Record of what it didPartialChat historyEvery action with its reason

What you are actually agreeing to

  • Least-privilege access

    Each agent gets its own scoped login with only the permissions its job needs. No shared admin accounts.

  • Every action logged, your limits enforced

    Each action is recorded with what the agent saw and why it acted. You set the approval thresholds — dollar amounts, new customers, price changes.

  • Your data stays yours

    We never use your data to train models. NDAs are standard on every engagement.

How it's built (for your IT lead)

Scoped service users, one per agent

Each agent authenticates as its own service user with least-privilege roles in your systems. No shared admin account, and access is revoked in one place.

An action log you can audit

Every action stores the input, the decision, the rule applied, the approver and the timestamp. The log is exportable.

Kill switch and dry runs

A kill switch per agent, and a dry-run mode for any new write action so you can see the effect before it happens for real.

Built for your process, not ours

The scaffolding underneath is shared — the connections, the customer and item map, the log. The agent itself is written around how your team actually works: your approval points, your part numbers, your exceptions. It is not an out-of-the-box agent you have to bend your process around.

Questions & Answers

FAQs

No. It's how we build and run your agents — the shared connections to your systems, the rules, the memory and the action log underneath them. You don't buy a platform licence and nobody on your team logs into anything new.

You keep your data and the action log. We agree the exit terms up front, including handing over documentation of every rule and every connection we built.

We choose per job and change them as better ones arrive — the model is an implementation detail, not something you're locked into. Your data isn't used to train any of them.

An agent can only use the permissions its own login has, it cannot exceed the limits you set, and every action it takes is logged with the reason for it. Anything unusual stops and asks a person.

No. Your systems stay the record. The agents work in them the way your team does — reading, drafting and writing through their own scoped logins.

Bring one process and we'll tell you straight

A working session on your real documents. You leave knowing whether an agent can do the job, and what counts as done.