🔁

Legacy System AI Automation

Automate the manual work around old or fragmented systems — no full replacement required.

Many companies run valuable but outdated systems that are risky or expensive to replace — so employees become the integration layer between them. We design AI workflows that connect to existing systems and automate the manual work around them: reading documents, checking statuses, preparing responses, creating tasks, updating records.

Process discoverySystem & data mappingCross-system data movement automationDocument processing around legacy systemsStatus checks & response preparationCase routingHuman approval & audit boundariesPilot-first delivery
Why it matters

Practical AI before transformation: a path to AI adoption with measurable pilots — while critical systems stay untouched.

Key capabilities

What Legacy System AI Automation covers

Process discoverySystem & data mappingCross-system data movement automationDocument processing around legacy systemsStatus checks & response preparationCase routingHuman approval & audit boundariesPilot-first delivery
How we work

What this direction delivers

Built on Agent Layer

Agent Layer is the productized execution foundation; this direction delivers discovery, integration, and client-specific implementation on top of it.

Low transformation risk

Core systems remain in place; automation grows around them in controlled steps.

Delivery approach

Five steps

01

Process discovery

Find the process where manual effort is highest and value easiest to measure.

02

System & data mapping

Where information lives and how work actually moves.

03

Automation design

What AI reads, extracts, prepares, updates — and what stays under human approval.

04

Pilot

A focused workflow, team, and system scope with measurable indicators.

05

Scale

Expand to more processes and teams — gradual and controlled.

Where it works

Use cases that make the difference

Insurance operations

Claims intake, status updates, policy servicing, broker communication around legacy cores.

Service & back office

Email classification, response drafting, ticket creation, approval routing.

Best fit
Legacy-heavy enterprisesInsurersFinancial servicesPublic sector
Outcome

Faster operational execution, reduced manual workload, lower transformation risk — a practical path to AI adoption without replacing critical systems.

Common questions

FAQ

Our core is too risky to touch. Can we still automate?

Yes — that is the point. AI workflows connect around the legacy system: reading documents, checking statuses, preparing responses, updating records via existing interfaces. The core stays untouched.

How is this different from RPA?

RPA replays clicks and breaks when screens change. This is AI-driven automation with understanding: document extraction, intent classification, cross-system reasoning — with human approval on judgment calls and an audit trail.

What if we plan to replace the legacy system eventually?

The automation survives the replacement: workflows, extracted data structures, and process knowledge transfer to the new core. Many clients use it as a controlled bridge — value now, lower-risk migration later.

Goes well with

Related products

See all in Custom Engineering

Start with a scoped pilot

One workflow, one team, measurable outcomes — scale follows proven value.