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Solutions

Systems we design, build and support

Each area below describes the problem it addresses, where it typically applies, how the work is carried out and what it connects to. Most projects combine two or three of them.

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01

AI Workflow Automation

Automation for processes that are currently held together by manual steps, spreadsheets and email.

What it solves

Work that repeats daily or weekly, depends on one person remembering the sequence, and produces no record of what happened. The cost is usually not the effort itself but the delay and the errors that surface later.

Integration possibilities

  • Email and file storage
  • Databases and internal APIs
  • Third-party SaaS APIs
  • Notification channels

Typical use cases

  • Document intake, extraction and filing
  • Recurring report preparation and distribution
  • Order, invoice or ticket routing based on rules
  • Data quality checks before a downstream process runs

How it works

  1. 01 The existing process is documented step by step, including the exceptions people handle informally.
  2. 02 Steps are separated into deterministic logic, integrations and the few places where a model adds value.
  3. 03 The workflow runs on a schedule or an event, with retries, an exception queue and a log of every run.
  4. 04 Operators keep a way to intervene: manual re-run, override and visibility into what a run did.
02

Custom Business Applications

Web applications built for a specific operational process rather than adapted from a generic product.

What it solves

Processes that have outgrown spreadsheets but do not fit an off-the-shelf system, where the workaround has become the process and no one has a reliable view of current state.

Integration possibilities

  • Existing databases
  • Identity providers
  • Payment providers
  • Reporting and export targets

Typical use cases

  • Operations and case management systems
  • Quotation, order and job tracking
  • Customer-facing portals for status and documents
  • Internal approval and review flows

How it works

  1. 01 The data model comes first: entities, states and the transitions that matter to the business.
  2. 02 Screens are built around the tasks people actually perform, in the order they perform them.
  3. 03 Authentication, permissions and audit trails are part of the initial build.
  4. 04 Deployment, backup and recovery are defined before the system holds real data.
03

Data & API Integration

Reliable movement of data between systems that were never designed to work together.

What it solves

The same data maintained in several places, reconciled by hand, with no agreement on which system is authoritative. Integrations that exist but fail silently.

Integration possibilities

  • REST and webhook APIs
  • SQL databases
  • Object storage and file transfer
  • Message and queue services

Typical use cases

  • Synchronising records between operational systems
  • Consolidating data for reporting
  • Ingesting third-party or partner data feeds
  • Exposing internal data through a controlled API

How it works

  1. 01 Source and destination systems are documented with their real constraints: rate limits, schemas, authentication, delivery guarantees.
  2. 02 One system is designated authoritative for each field, and conflict handling is defined explicitly.
  3. 03 Transfers are idempotent where possible, so a re-run does not duplicate or corrupt data.
  4. 04 Failures raise an alert with enough context to diagnose, rather than disappearing into a log file.
04

AI Model Integration

Language and document models applied to defined tasks inside existing systems, with checks around them.

What it solves

Tasks where a model is genuinely useful — reading unstructured text, classifying, drafting — but where an unmonitored chatbot would create more work than it removes.

Integration possibilities

  • Hosted AI APIs
  • Document and content stores
  • Review and approval interfaces
  • Existing business applications

Typical use cases

  • Extracting fields from contracts, invoices or forms
  • Classifying and routing inbound messages
  • Summarising long documents for review
  • Drafting responses that a person approves before sending

How it works

  1. 01 The task is narrowed until output can be validated, either automatically or by a reviewer.
  2. 02 Prompts, model choice and parameters are versioned alongside the application code.
  3. 03 Outputs are validated against a schema, and low-confidence cases are routed to a person.
  4. 04 Cost, latency and error rates are logged per call so the approach can be evaluated honestly.
05

Internal Tools & Dashboards

Operational visibility for the people who run the process day to day.

What it solves

Decisions made from exported spreadsheets that are already out of date, and questions that require a developer to answer because the data is only reachable through a database client.

Integration possibilities

  • Application and analytics databases
  • Internal APIs
  • Identity and access management
  • Email and messaging for scheduled output

Typical use cases

  • Operational status and throughput dashboards
  • Admin tools for support and back-office teams
  • Data correction interfaces with an audit trail
  • Scheduled reporting to email or storage

How it works

  1. 01 The questions the tool must answer are agreed first, which usually reduces the number of screens required.
  2. 02 Queries are shaped for the access pattern rather than reporting on raw tables.
  3. 03 Write actions are permission-controlled and recorded.
  4. 04 Access is reviewed as part of handover, not left open by default.
06

Process Digitalisation

Paper, PDF and email-based processes moved onto structured systems.

What it solves

Processes where the record of what happened lives in an inbox or a filing cabinet, making review, reporting and compliance work slow and unreliable.

Integration possibilities

  • Document storage
  • Email and notification services
  • Existing systems of record
  • Export for accounting or compliance

Typical use cases

  • Form and request submission with structured storage
  • Digital approval chains replacing email threads
  • Document generation from structured data
  • Status tracking visible to everyone involved

How it works

  1. 01 The current paper or email trail is turned into an explicit state machine.
  2. 02 Data is captured once, validated at entry, and reused downstream instead of retyped.
  3. 03 Documents are generated from the same data that drives the process.
  4. 04 Historic records are migrated or archived deliberately, with retention agreed up front.

Not sure which of these applies?

Describe the process you are looking at and we will tell you which approach fits, or whether the problem is better solved without new software.

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