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Agent Layer

AI agents on top of your existing systems — no core replacement.

An AI agent layer that automates back-office work on top of the client's existing systems: core platforms, CRM, ticketing, document repositories, email, databases, APIs, and legacy interfaces. A lot of operational inefficiency happens between systems: search, copy, verify, update, forward, summarize. Agent Layer makes that work faster and safer, without replacing the core platform.

Back-office · 13:20
A broker submission just arrived by email. Can you process it?
Agent Layer
Read and classified it, extracted the policy and customer fields, checked the core system for duplicates, and prepared a pre-filled record. One field is missing (start date) — flagged for your review before I create it.
Platform highlights

Why teams choose Agent Layer

Intake & classification

Reads, classifies, and prepares incoming emails, documents, and forms for action.

Cross-system lookup

Finds customer, policy, claim, or invoice data across multiple internal systems.

Record updates

Creates tasks and tickets, updates CRM and core systems, maintains audit trails.

Exception routing

Routes the cases that need a person to the right team.

Agent assist

Shows context, suggests next-best-action, drafts messages during live work.

Human-in-the-loop

Sensitive, compliance, and high-value steps stay under human approval.

Where it works

Use cases that make the difference

Incoming request automation

Turn inbound emails and documents into ready-to-action records.

Cross-system back office

Eliminate copy-verify-update work between systems.

Legacy without replacement

Automate around old systems instead of replacing them.

Common questions

FAQ

What is the Agent Layer?

An AI agent layer that automates back-office work on top of your existing systems, without replacing the core.

Why not just replace the old systems?

Much inefficiency happens between systems; Agent Layer makes that work faster and safer without a rip-and-replace.

What does it connect to?

Core systems, CRM, ticketing, document repositories, email, databases, APIs, and legacy interfaces.

What work does it automate?

Intake and classification, cross-system lookup, record updates, drafting, and exception routing.

Does it keep humans in control?

Yes. Sensitive, compliance, and high-value steps stay under human approval.

Can it assist live agents?

Yes. It shows context, suggests next-best-action, and drafts messages during live work.

Where is our data stored?

In the EU by default, with an on-premise option, inside your perimeter.

How does it handle exceptions?

It routes cases that need a person to the right team, with an audit trail.

How long to deploy?

A two-week proof of concept on one process, then four to eight weeks to production.

How is it priced?

Platform license plus implementation, scaling with processes and connected systems.

Goes well with

Related products

See all in AI Products

Try it on your data

Two weeks. Your environment. A working proof of concept under NDA — see the impact before any commitment.