AI Development

AI Application Development for Real Business Workflows

We build AI-powered applications and features that read documents, classify requests, draft content and surface insights — integrated with the systems you already run.

From model to useful application

An AI model on its own is a capability, not a product. AI application development is the work of turning that capability into something your staff or customers use every day: a screen in your existing system that pre-fills an invoice, a queue that sorts incoming emails, a search box that actually understands the question.

This service sits within our wider AI development practice and focuses on targeted AI features and focused applications. If you need a full web platform built around AI, see AI web application development.

Common AI applications we build

Document processing

Extract fields from invoices, purchase orders, delivery notes, contracts and application forms. We combine OCR, large language models and validation rules so outputs are checked against your master data before they reach your ERP or accounting system.

Classification and routing

Automatically categorise support tickets, emails, claims or leads by topic, urgency and sentiment, then route them to the right team. Typical accuracy on well-defined categories is 90%+, with low-confidence items flagged for a human.

Summarisation and drafting

Summarise long case files, meeting transcripts or customer histories; draft replies, reports and product descriptions in your tone of voice for staff to review and send.

Replace keyword search with search that understands meaning, across policies, product catalogues, technical manuals or past projects.

Prediction and forecasting

Classic machine learning still has its place: demand forecasting, churn risk, anomaly detection and lead scoring on your historical data.

Engineering for reliability

  • Evaluation sets built from your real examples, so accuracy is measured, not assumed
  • Confidence thresholds and human review queues for uncertain results
  • Structured outputs validated against schemas before anything is written to a database
  • Cost controls: caching, batching and routing simple tasks to smaller models
  • Audit logs of inputs, outputs and user corrections, which also feed continuous improvement

Integration matters most

The AI component is often 20–30% of the effort. The rest is integrating with your ERP, CRM, document storage and identity systems, and designing a review interface that staff trust. That is where our background in custom software development makes the difference.

    • What you get

      • AI feature or application

        Deployed and integrated with your existing systems.

      • Evaluation report

        Measured accuracy, failure modes and cost per transaction.

      • Review interface

        Screens for staff to check, correct and approve AI output.

      • Monitoring dashboard

        Live view of volumes, confidence, corrections and spend.

    • Industries we serve

      • Finance

        Secure software for lenders, brokers, accountancy practices and fintech teams: client portals, workflow automation, reporting and integrations with financial systems.

      • Logistics

        Fleet tracking, driver apps, dispatch and warehouse software for logistics, courier and distribution companies that need live visibility and proof of delivery.

      • Professional Services

        Client portals, CRM, project and time tracking, billing and AI-assisted document workflows for consultancies, agencies, law and accountancy firms.

    Benefits

    Why invest in ai application development

    • Less manual data entry

      Documents and emails are read and structured automatically, with humans reviewing only the exceptions.

    • Faster turnaround

      Requests are classified and routed in seconds rather than waiting in a shared inbox.

    • Consistent quality

      The same rules and tone are applied every time, reducing errors caused by fatigue or inexperience.

    • Improves over time

      User corrections are captured and used to refine prompts, examples and models.

    Capabilities

    What we build and deliver

    • Intelligent document extraction

      OCR plus LLM extraction with field-level validation against your master data.

    • Text classification

      Topic, intent, urgency and sentiment labelling with configurable confidence thresholds.

    • Summaries and drafts

      Concise summaries and first drafts generated in your house style for staff review.

    • Semantic search

      Vector search over your content with filters that respect user permissions.

    • Forecasting models

      Machine learning models for demand, churn and anomaly detection on historical data.

    • Human review queue

      A simple interface to approve, correct or reject AI output, with every decision logged.

    Process

    How we deliver

    A transparent, milestone-based process with working software at every stage.

    • Use-case definition

      Collect real examples, define success criteria and agree which decisions stay with humans.

    • Evaluation dataset

      Build a labelled test set from your data so every design choice can be measured.

    • Prototype and benchmark

      Compare prompts, models and pipelines against the test set and report accuracy and cost per item.

    • Integrate and harden

      Connect to source and target systems, add review screens, validation, logging and error handling.

    • Monitor and refine

      Track accuracy drift, review corrections and tune the system on a regular cadence.

    Technologies

    Technology we use for this service

    • AI & Machine Learning

      Applied AI and machine learning for forecasting, classification, recommendations and document understanding, alongside large language models where they add value.

    • OpenAI

      We integrate OpenAI models into business software for assistants, document processing, search and content workflows, with grounding, evaluation and cost controls.

    • Anthropic Claude

      We build AI assistants, agents and document workflows on Anthropic's Claude models, known for long-context reasoning, careful instruction following and strong writing.

    • .NET

      We use Microsoft .NET to build fast, secure and maintainable business software: web APIs, ERP and POS back ends, background services and cross-platform apps.

    • Microsoft Azure

      We design, build and run applications on Microsoft Azure: App Service, containers, Azure SQL, Functions and Azure OpenAI, with security and cost control built in.

    Related work

    Projects we've delivered

    • AI Sales Assistant for B2B Teams

      An LLM-powered sales assistant that qualifies inbound leads, drafts tailored follow-ups and summarises accounts from CRM data for a B2B industrial supplier.

    • Manufacturing ERP Rollout

      A custom ERP for a mid-sized metal fabrication manufacturer, connecting sales orders, production planning, inventory, purchasing and finance in one system.

    • Clinic Appointment Mobile App

      A patient booking app and clinic scheduling back office for a group of private outpatient clinics, with online booking, reminders and secure pre-visit forms.

    Case studies

    Results from similar engagements

    • AI Support Assistant for a B2B SaaS Company

      How a B2B SaaS company deployed a grounded AI support assistant that resolves 42% of conversations on its own and hands the rest to agents with full context.

    • Retail Chain POS Modernisation

      How a 60-store retail chain replaced ageing on-premise tills with an offline-capable cloud POS, cutting checkout times by 35% and ending overnight price syncs.

    What our clients say

    • We used to lose half a day's takings every time a store's broadband went down. Since the new tills went in, outages barely register, and head office can change a price at lunchtime and see it on every shelf-edge promotion by the afternoon.

    • Parents now have one app instead of four, and our office teams have stopped spending Monday mornings chasing absence calls. The migration was the part we worried about most, and the trial runs meant there were no surprises on go-live day.

    • The assistant resolves the repetitive how-do-I questions and hands everything else to us with a proper summary. Our agents spend their time on the tricky tickets now, and customers get answers at 2am without us adding a night shift.

    Solutions

    Related software solutions

    • AI Business Automation

      AI business automation platform that reads documents, classifies requests and runs multi-step workflows across your systems, with human approval where it matters.

    • Accounting Software

      Accounting software for SMEs and multi-entity groups: ledgers, invoicing, bank reconciliation, VAT and tax, approvals and management reporting, integrated with your operations.

    • AI Customer Support

      AI customer support assistant that answers questions from your own knowledge base, takes actions through your systems and hands off to human agents with full context.

    FAQ

    Frequently asked questions

    • What is the difference between an AI application and an AI agent?

      An AI application usually performs a defined task — extract, classify, summarise — within a fixed workflow. An AI agent decides which steps and tools to use to reach a goal. Many projects start with applications and add agent behaviour later.

    • How accurate is AI document extraction?

      On consistent document types we typically see 90–98% field-level accuracy after tuning. Validation rules and a human review queue catch the remainder, so errors do not flow into your systems.

    • Can you add AI features to our existing software?

      Yes. We often add AI as a separate service that your existing application calls through an API, which avoids a risky rewrite of the core system.

    • How do you control AI running costs?

      We measure cost per transaction from the prototype stage, route simple tasks to smaller models, cache repeated work and batch non-urgent jobs. Costs are visible on a dashboard in production.

    Insights

    Further reading

    Have a process AI could speed up?

    Send us a few real examples and we will tell you honestly whether AI can handle them reliably.

    Talk to an Expert

    Send us a few real examples and we will tell you honestly whether AI can handle them reliably.

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