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Cloudus Infotech
AI · Prompt Engineering

Prompts treated as versioned code, not copy

Prompt design, versioning and regression testing, so a change that improves one case cannot quietly break ten others.

Scope a two-week POCAll AI capabilities

  • 2 wks

    To a working POC

  • 15

    AI capabilities we build

  • 9

    Years in business

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OverviewProcessStackMore AIFAQ

What you get

What every prompt engagement includes

A prompt is a piece of software. We version it, test it and measure it like one.

Talk through the use case

Prompts in version control with change history

A test set that runs on every prompt change

Structured output the application can rely on

Our process

Four steps from rough prompt to tested prompt

Every change is scored.

  1. 01

    Collect real examples

    Good and bad cases from your work, which become the test set.

  2. 02

    Write & structure prompts

    Instructions, examples and output formats, written for the task.

  3. 03

    Test & compare

    Variants scored against the same cases, across models where it helps.

  4. 04

    Version & hand over

    Prompts in your repository, with the tests and notes to maintain them.

Tech stack

What we build it with

Four layers, each chosen per project. Open one to see what sits in it and why.

Models & frameworks

The layer that generates. Chosen per task against quality, latency and cost.

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More AI capabilities

Fourteen more ways we apply AI

AI Software Development

End-to-end AI product builds.

AI Chatbot Development

Smart, conversational AI for business.

AI Agents Development

Linked agents for smarter tasks.

AI Voice Agents

Voice intake and call handling.

Generative AI Solutions

AI that creates and innovates.

LLM Chatbot Development

Grounded in your own content.

LLMs for SMEs & Enterprises

AI built to scale with you.

RAG Model Development

Smarter AI with search + generation.

GPT Integration

AI seamlessly in your workflow.

Machine Learning Development

AI that learns from your data.

NLP Development

Classification, extraction, sentiment.

AI Workflow Automation

Process automation that holds up.

AI MVPs & POCs

Proof before you commit to a build.

AI Consulting

Where AI pays off, and where it doesn't.

Frequently asked questions

The questions we get asked about AI

Data handling, output quality, cost and ownership.

Yes. We score what you have, show where it fails and fix those cases first.

They can. Because every prompt has a test set, we re-run it on a new model version and see exactly what changed.

A POC on one workflow runs two weeks. A production build on top of it is typically 6–12 weeks, delivered in increments you can use.

Fixed price against a written scope for the POC, then fixed scope or a monthly dedicated-team rate for the build. Cost per request is established before we scale.

You do, from day one. Repositories, prompt history, evaluation sets and infrastructure accounts are all in your name.

Send us the workflow you want to automate. We come back within one business day with questions, then a written scope and a cost per request.

Start with the prompt that matters most

Two weeks, your prompt scored and improved against real examples.

Start the POC