AI Integration

Practical AI inside your product

AI is only useful when it does a job your users care about. I build assistants, classifiers and automation that reduce real work — with the cost per request worked out before we start, so there are no surprise invoices.

Get a quote → How it works

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From $900Fixed quote

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2–5 weeksTypical timeline

What makes this different

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Keys stay server-side

The API key never reaches the browser. Every request is proxied through your backend.

₹

Costs modelled upfront

You see the price per request and per month before a line of code is written.

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Guard rails

The model is scoped to its job and declines what falls outside it, rather than guessing.

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Caching and limits

Common answers are cached and context is capped, which typically cuts spend by half.

How a ai integration project runs

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01Understand

Work out which task AI should do, and whether it is worth automating

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02Design

Prototype against your real data, not a demo dataset

03Build

Build the proxy, guard rails, caching and rate limits

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04Launch

Ship with a usage dashboard so you can watch the cost

What you receive

Working AI feature in your product
Server-side proxy and key management
Usage and cost dashboard
Prompt documentation you can edit
10 days of tuning after launch

Built with

OpenAI APILangChainPythonNode.jsRedisVector searchWebhooks

Questions about ai integration

?Which model do you use?›

Whichever fits the job and budget. For most tasks a smaller, cheaper model performs as well once the prompt is right.

?What does it cost to run?›

Depends on volume. A support assistant handling 5,000 messages a month typically runs $20–60 in API costs.

?Is our data used for training?›

No. Business API tiers exclude your data from training, and I configure that explicitly.

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Need ai integration?

Tell me what you are trying to build and get a fixed quote.

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