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Automate the workflows that rule-based tools can't touch.

Agentic AI that reads context, makes decisions and executes multi-step processes end to end — without a human in the loop for every action.

Book a scoping session See the problem

The problem

When rpa breaks on every exception becomes the norm

  • RPA breaks on every exception

    Rule-based automation works until something changes. Then it fails silently or creates more manual work to clean up.

  • Processes that cross too many systems

    Workflows that touch 4+ systems require human coordination at every handoff. No tool connects them end to end.

  • Backlogs that never shrink

    High-volume, repetitive operational tasks pile up faster than teams can clear them. Hiring doesn't scale fast enough.

How it works

Agents that read context, decide, and execute—without brittle scripts

Step 1

Map the workflow

We connect systems, documents, and policies so the agent knows what "done" means and what is off-limits.

Step 2

Run with guardrails

Multi-step execution with human checkpoints, tool use, and audit trails—so automation stays inside your risk envelope.

Step 3

Observe and harden

Production telemetry on failures, rework, and exceptions feeds back into prompts, tools, and escalation rules.

Sequences are adapted to your ERP, ticketing stack, and approval matrix.

Automate the workflows that rule-based tools can't touch.

What's included

What you get when you run this with Thinkia

A governed layer across data, workflows, and handoffs—so teams ship safely and scale with metrics.

Multi-step agent orchestration

agents that plan, execute and adapt across complex workflows without predefined rules for every state

System integration layer

connects to your existing stack (ERP, CRM, HRIS, custom APIs) without ripping and replacing

Exception handling with judgement

when a process hits an edge case, the agent escalates intelligently instead of failing silently

Human-in-the-loop controls

define which decisions require human approval and which can run autonomously

Process observability

full audit trail of every action taken, every decision made and every exception raised

Workflow cloning

once a process is automated, replicate it across business units with minimal reconfiguration

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Results

What changes when this runs in production

–60%

Average reduction in end-to-end time for automated workflows

<5%

Share of runs requiring human intervention after tuning

3–5

Typical number of production-ready automations in first engagement

Results vary by process complexity, system landscape and data quality.

How we work

From workflow map to governed agents in production

Map & prioritise

Week 1–2

We trace systems, approvals, and failure modes so automation targets the right steps—not every step.

Design agents & tools

Week 3–5

Prompts, tools, checkpoints, and escalation paths are defined against your policies and audit needs.

Shadow & pilot

Week 6–9

Runs in parallel with humans; we measure rework, exceptions, and latency before widening scope.

Scale & harden

Week 10+

Roll out by domain, tune playbooks, and lock observability so ops owns the loop long term.

Depth of integrations and number of tools drive duration; scope is fixed before dates are committed.

Get started

Ready to scope this for your context?

We start with a focused session—no commitment—to map constraints and a sensible path.

Book a scoping session Explore AI Solutions