AI Workflow Automation
Document processing, triage, and internal workflow automation using AI where it fits and conventional logic where it does not.
- Baselined
- Measured against current process
- Audited
- Every decision logged
- 4-10 wk
- Typical build
About ai workflow automation
The highest-return AI work is usually invisible to customers: extracting fields from invoices, routing support tickets, summarising long documents, checking submissions against criteria. Repetitive, high volume, and currently done by people who would rather be doing something else.
AI for judgement, rules for the rest
Effective automation mixes both. Use the model where the input is unstructured and judgement is required; use deterministic logic where the rules are clear. Applying a model to something a conditional statement handles reliably adds cost and unpredictability for no benefit.
Human review calibrated to consequence
Not every decision needs review, and not every decision can go unreviewed. We calibrate to consequence: high-confidence, low-impact decisions proceed automatically; uncertain or high-impact ones route to a person with the model’s reasoning attached.
Measured against the current process
Success is throughput, error rate, and cost compared with what happens today — not model accuracy in isolation. We baseline the existing process first so the comparison is honest.
What the engagement includes
Document processing & extraction
Structured fields pulled from invoices, forms, and contracts.
Classification & triage
Tickets, emails, and submissions routed automatically.
Summarisation
Long documents and threads condensed for faster review.
Human-in-the-loop review
Confidence-based routing with reasoning attached.
Audit logging
Every automated decision recorded and reviewable.
What you get
The measurable results this service is accountable for.
- Repetitive processing handled at a fraction of the time
- Human review targeted where consequence justifies it
- Deterministic logic where rules are clear
- Measured against your current process baseline
- Audit trail of automated decisions
A process without surprises
Clear checkpoints at every stage, so you always know what is shipping and when.
- 1
Discovery & feasibility
We assess the use case, data readiness, and whether AI is genuinely the right tool before proposing a build.
- 2
Prototype & evaluation
A working prototype measured against defined accuracy and cost criteria, so the decision to proceed is evidence-based.
- 3
Production build
Hardening, guardrails, monitoring, evaluation harness, and integration with your systems.
- 4
Monitor & improve
Ongoing quality monitoring, prompt and retrieval tuning, and model updates as the landscape changes.
What is included at each tier
Engagements scale with your stage. Every tier includes everything below it.
| What's included | Starter | Growth | Enterprise |
|---|---|---|---|
| Process baseline & assessment | Included | Included | Included |
| Prototype automation | Included | Included | Included |
| Production workflow build | Not included | Included | Included |
| Human review interface | Not included | Included | Included |
| Audit logging & reporting | Not included | Not included | Included |
Sectors we work in
We use AI only where judgement is genuinely needed, and route decisions to humans in proportion to their consequence.
Common questions
What if the AI gets it wrong?
Will this replace our staff?
More ai development & consulting services
Ready to talk about ai workflow automation?
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