Your team is spending hours every week on work AI should be doing.
Approvals, data entry, report generation, request routing — these processes run on manual effort that AI can handle automatically. We build AI process automation that replaces the repetitive work, handles exceptions cleanly, and runs in the background while your team focuses on what matters.
Which processes are eating your team's time?
Every automation is built around a specific process — scoped, priced, and delivered as a finished product that runs in your environment.
Approval routing automation
Route purchase orders, leave requests, and compliance approvals to the right person based on value, team, and policy — without manual triage.
Document processing pipelines
Read incoming documents (invoices, forms, contracts), extract the data fields you need, validate them, and push to your target system automatically.
Report generation automation
Pull data from multiple sources on schedule, generate formatted reports, and distribute them — without anyone spending hours in spreadsheets.
Inbound request triage
Read incoming emails, tickets, or form submissions, classify the request type, extract key information, and route to the right team with context.
Onboarding workflows
Trigger multi-step onboarding sequences across HR, IT, and operations systems automatically when a new employee, customer, or supplier is added.
Compliance monitoring
Check records, documents, and system states against policy rules on a schedule. Flag violations, generate audit trails, and escalate exceptions automatically.
From manual process to running automatically
Process audit
We map the current process — inputs, decisions, systems touched, exception types, and volume. This defines the automation scope.
Automation design
We design the AI logic, integration points, exception handling rules, and human review triggers. You approve the design before build starts.
Build and test
We build the automation against real process examples, test against edge cases, and validate that exceptions route correctly.
Live in production
The automation runs in your environment, connected to your systems. You see the results. Manual work drops. Volume handled rises.
Questions about AI process automation
What is AI process automation?
AI process automation uses large language models and workflow orchestration to handle multi-step business processes that previously required human intervention. Unlike traditional rule-based automation (which breaks when inputs vary), AI process automation can read unstructured inputs, make contextual decisions, handle exceptions, and complete tasks even when data formats change. It handles the judgement calls that rigid automation can't — routing an ambiguous request to the right team, extracting data from a non-standard document, or deciding whether an approval request meets policy criteria.
How is AI process automation different from RPA (Robotic Process Automation)?
Traditional RPA tools like UiPath or Automation Anywhere automate fixed, repetitive sequences — they click through a UI or follow a rigid script. They're brittle: when the interface changes, they break. AI process automation handles variation. It can read a PDF invoice in any format, understand an email request written in natural language, decide which approval path to take based on context, and handle exceptions without manual intervention. For structured, never-changing processes, RPA can work fine. For anything that involves unstructured inputs, variable formats, or contextual decisions, AI automation is far more robust.
What types of business processes can AI automate?
AI process automation works well for: approval and exception routing (purchase orders, leave requests, compliance sign-offs); document processing pipelines (invoices, contracts, application forms); data entry and system updates (pulling data from emails or documents and updating CRMs, ERPs, or databases); report generation (pulling data from multiple sources, summarising, formatting, and distributing on schedule); customer request triage (reading inbound emails or tickets and routing to the right team with context); onboarding workflows (collecting information, triggering actions in multiple systems, sending communications); and compliance monitoring (checking records against policy and flagging violations).
Which systems can AI process automation connect to?
Any system with an API, webhook, or accessible data layer. We commonly integrate with Microsoft 365 (Outlook, Teams, SharePoint), CRMs (Salesforce, HubSpot, Pipedrive), accounting systems (Xero, Sage, QuickBooks), ERPs (SAP, NetSuite, Dynamics), HR systems (BambooHR, Workday), project tools (Jira, Asana, Monday), databases (SQL, Postgres, Supabase), and custom internal applications. If a system doesn't have an API, we can use email, file-based integration, or browser automation where necessary.
How quickly can AI process automation be implemented?
A single, well-scoped automation typically takes 2–4 weeks from kickoff to production. Simple automations involving one document type or one decision point can be live in under two weeks. Complex multi-step automations with several integrations, exception handling logic, and approval chains typically take 4–6 weeks. We scope the exact timeline and deliverables before any work starts — so you know what you're getting and when.
What does AI process automation cost?
Most AI process automation projects are priced between £8,000 and £20,000 fixed price, depending on complexity and number of system integrations. A single-process automation (e.g., invoice processing or approval routing) typically starts from £8–12K. A multi-process automation suite with several connected workflows and integrations typically ranges from £15–20K. All projects are priced fixed upfront — no hourly billing, no scope creep invoices.
What happens when the process has exceptions or edge cases?
We design exception handling into every automation we build. When the AI encounters a situation it can't resolve confidently — an ambiguous approval, a missing data field, an unusual document format — it routes the exception to a human with full context rather than failing silently or passing through incorrect output. You can configure the threshold: how much ambiguity triggers human review. Most automations run 85–95% of cases automatically, with the remaining edge cases handled cleanly in a review queue.
Do we need to change our existing systems or processes?
No. We build the automation to fit around your existing systems and workflows, not the other way around. Your teams continue using the same tools; the automation runs in the background handling the parts that don't need human involvement. We don't require a system upgrade, a data migration, or a process redesign before we can start. We scope the automation based on what you have today.
Tell us which process is costing your team the most time.
Describe the manual process — the inputs, the steps, the systems involved. We'll scope exactly what AI can automate and send a fixed-price build plan within 24 hours.
Get a Fixed-Price Quote