Automation and AI for everyday business workflows.
We build automation and AI-assisted applications for teams processing documents, searching internal knowledge and using historical data to support decisions. Work can fit into your existing tools or form part of a new application. We choose the approach around the task, keeping validation, permissions and human review in the workflow where they are needed.
Four approaches
Start with the task and the information available. A known rule may need ordinary software; varied documents, knowledge questions and predictions need different methods and checks.
| Approach | Task | Input | Output | Review considerations |
|---|---|---|---|---|
| Rules-based automation | Route, check or schedule a known action. | Structured records and explicit rules. | A routed request, validation result or scheduled action. | An owner handles exceptions when the rule cannot be applied. |
| Extraction and classification | Identify fields or classify incoming information. | Documents, forms or messages with varying layouts and wording. | Proposed fields or a suggested category. | Validate against the source before authorised approval. |
| Knowledge retrieval | Find information relevant to a question. | Permitted documents with maintained versions and ownership. | An assisted answer connected to its sources. | Check access and evidence; acknowledge missing information. |
| Predictive analysis | Estimate an outcome to support a defined decision. | Relevant historical data and a measurable target. | A forecast or likely outcome. | Compare with a baseline and monitor usefulness over time. |
Document extraction
An extracted field is a proposal. Review it beside the source, resolve mismatches, then pass the record to authorised approval. The invoice comparison shows why those are separate steps.
Missing pages, conflicting values and unreadable scans need recovery paths. Keep each proposed value connected to its original material so reviewers can investigate it.
Inspect the source before accepting the field.
Illustrative example. Sample records.
Source invoice
- Invoice number
- INV-0180
- Supplier
- Example supplier
- Issue date
- 4 October 2026
The original document remains available alongside the proposed record.
Extracted proposal
INV-0108
Review required: the extracted reference differs from the source.
The extracted reference transposes the final digits. A reviewer corrects this field against the source; other fields still need validation.
Approval remains separate. An authorised user reviews the record under the organisation’s rules before posting or payment.
Retrieval with sources
Retrieve passages from material the user may access, then connect the assisted answer to those sources. If suitable evidence is missing, say so. References let the reader inspect the answer's basis.
Enforce access during retrieval, not only on the final screen. Agree source ownership, versions, retention and updates, including how conflicting or obsolete documents are handled.
- Permitted material
- Retrieved passage
- Answer with references
Make the workflow dependable
Check usefulness
Agree what counts as useful and test ordinary inputs alongside missing values, ambiguous wording, conflicting sources and unexpected documents. Check whether fields are supported, relevant material is found and exceptions reach a reviewer; measure review effort and recoverable failure.
Prediction needs a defined target and historical data reflecting what was known at the time. Compare with an existing rule or estimate, monitor changes in the process and identify who acts on the forecast and its uncertainty.
Adoption and handover
Map the process before choosing a model, then start with a bounded workflow connected to the systems it will use. Help the team understand what to inspect and when to escalate.
Handover includes representative examples, evaluation material, operating limits and source-maintenance responsibilities. Extend automation using evidence from real use, with important records and decisions kept visible.