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What we build

Six ways we put AI to work inside your business

We scope every engagement to the problem in front of you — not a fixed package. Below is exactly what each service includes, how we price it, and the stack we build it on.

01 / AI Automation

Replace manual workflows with agents that act

We wire agents into the tools your team already uses — inboxes, ticketing systems, spreadsheets, internal dashboards — so they read incoming work, make a decision against rules you define, and take the action themselves. Every agent ships with a confidence threshold and a human hand-off path for anything it isn't sure about.

  • Workflow agents
  • RPA replacement
  • Inbox & ticket triage
  • Human-in-the-loop review
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02 / Machine Learning Systems

Custom models, trained on your data, owned by you

Forecasting, classification and recommendation models built specifically for your data shape — not a generic API wrapper. We hand over the training pipeline, the evaluation harness and the retraining schedule, so your team can improve the model long after we're gone.

  • Forecasting
  • Classification
  • Recommendation
  • Model evaluation harness
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03 / Data Engineering

One queryable source of truth, not twelve spreadsheets

We build the pipelines and warehouse layer that every AI system depends on: ingestion from your existing tools, cleaning and deduplication, and a schema your analysts and models can both query. This is almost always the first phase of a larger AI build.

  • ETL / ELT pipelines
  • Warehouse design
  • Data quality checks
  • Real-time streaming
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04 / Cloud & DevOps

A model update should be a one-click event

Infrastructure that scales with usage instead of guessing at it up front — containerised services, CI/CD pipelines, and monitoring wired in from day one. We set thresholds and alerting so failures get caught before they become incidents, not after.

  • CI/CD
  • Kubernetes
  • Infra as code
  • Observability
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05 / AI Strategy & Consulting

A clear-eyed audit before you spend a rupee building

Not every problem needs a model. We run a structured audit of your workflows, data readiness and team capacity, then hand you a prioritised roadmap of what's actually worth automating first — with estimated cost and payback period for each item.

  • Readiness audit
  • ROI modelling
  • Build vs. buy
  • Roadmap workshop
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06 / Custom AI Products

From prompt design to the UI your team logs into

End-to-end builds for teams who need a real product, not a proof of concept — RAG pipelines over your own documents, agent orchestration, and the front-end your team and customers actually use every day, all owned and documented on handover.

  • RAG pipelines
  • Agent orchestration
  • Product UI
  • API integrations
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