Custom GPTs, actions and OpenAI integrations — connecting ChatGPT to your systems with proper authentication, scoping and audit.
Delivered from our Chennai and Bengaluru studios — to clients across India and overseas.
// The problem
Setting up a custom GPT with instructions and uploaded documents takes an afternoon and is genuinely useful. The limit appears quickly: it cannot look up an order, check current stock, or file anything in your systems. It reasons well about information that is already stale.
The gap between that and something business-useful is not configuration — it is engineering. Authenticated access, operations scoped so the assistant can do exactly what you intend, and a record of what it did.
Does any of this sound familiar?
What it costs to leave this alone
A GPT that answers from stale data is worse than no GPT, because people trust it. Confident answers from last quarter's pricing reach customers, and the error is discovered downstream.
// How we fix it
We build custom GPTs with actions against your real systems — authenticated, narrowly scoped, and validated. The assistant requests operations; a layer you control checks permissions and executes them. Credentials never reach the model.
Grounding comes from your live data with citations rather than uploaded snapshots, refusal behaviour handles what it does not know, and logging shows what it did and what it cost.
Talk to us about your project// What changes
What you should expect to be different once this is in place.
Not uploaded
Answers from current systems, with citations, rather than a stale document set.
Per user
Each person sees what they are entitled to, enforced outside the model.
Usage and cost
Logging and attribution, so you can see what it does and what it costs.
// What's included
Instructions, knowledge and behaviour tuned for your specific use case and tested against real queries.
Authenticated API operations, narrowly scoped and validated, described so the model calls them correctly.
OAuth and API key handling that maps to the requesting user rather than a shared service credential.
Your documentation and data as the answer source, with citations rather than model recall.
Confidence thresholds and refusal behaviour so it declines rather than improvising.
Logging and cost attribution so you can see what it is doing and what it costs.
// Who this is for
Where the assistant is in daily use but disconnected from systems.
Where uploaded documents go stale too quickly to be safe.
Ticket creation, record updates, structured output into systems.
// Problems we've solved
Representative engagements, described in terms of what changed for the business.
A custom GPT answered product questions from a document uploaded months earlier, including pricing that had since changed.
Replaced uploaded files with live retrieval from the product system, with citations and a refusal path for anything not found.
Answers reflected current data, and the assistant declined rather than guessing when information was missing.
The team wanted the assistant to raise support tickets rather than describing how to raise them.
Built an authenticated action creating tickets with structured fields, requiring confirmation before submission.
Tickets were created from the conversation with the human approving, removing a manual re-entry step.
// Technology
Chosen for durability and fit — and handed over as documented code you own outright.
// Questions
// Read before you commit
Honest, detailed writing on costs, trade-offs and how to choose — including when not to hire us.
Scoped access, permission mapping, audit trails and prompt-injection defence — the architecture that makes AI access to internal systems defensible to your security team.
Read moreWhat function calling and tool use mean in practice, how tools should be scoped and validated, and why bad tool design is the most common cause of unreliable agents.
Read moreHow to evaluate models for a production use case — capability fit, cost, latency, context, data policy — rather than picking by benchmark leaderboard.
Read more// Explore more
Most clients start with one service and grow into others. One team owns the whole stack.
// Start a project
Free consultation. Honest scoping. A fixed quote within 48 hours.