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Service 03 / 06

AI applications

Useful AI features are mostly careful engineering: clear inputs, predictable outputs and a fallback when the model is wrong. We build AI-assisted features and agent tooling, including MCP servers that let assistants act inside your existing systems.

  • TypeScript
  • Python
  • MCP
  • Cloudflare Workers
  • Hono

What is included

A typical engagement

Every project is scoped individually; this is the usual shape of the work.

  1. Identifying tasks where AI genuinely saves time
  2. Model Context Protocol (MCP) servers and tool definitions
  3. Prompt and output design with validation
  4. Human review steps where accuracy matters
  5. Cost and latency considerations documented up front

How we approach it

  • Start with one well-defined workflow, not a general chatbot.
  • Validate model output before it reaches users or other systems.
  • Keep the non-AI path working so the product degrades gracefully.

A good fit when

  • Teams that want assistants or agents to use their internal tools
  • Products adding a focused AI feature
  • Repetitive content or media workflows that can be automated

Not sure it fits?

Describe the problem rather than the solution. We will tell you honestly if a different approach, or a different studio, would serve you better.

Start a conversation

Related work

Where we have done this before

Public projects that use the same kind of engineering. Labels show whether each is an in-house product, open source, community work or a concept demo.

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Next step

Have an idea worth building?

Tell us what you are working on. You will hear back from the founder directly, usually with questions before a quote.

Start a projectEmail sh20raj@gmail.com