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Cloudus Infotech
AI · Generative AI Solutions

Generation constrained by your rules, not the model’s defaults

Drafting, summarising and asset creation that follows your tone, your templates and your approval process.

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 generative AI build includes

Generated content needs guardrails. We agree style, sources and review before the first output reaches a customer.

Talk through the use case

Your templates and tone encoded as constraints

Human approval where output carries brand or legal risk

Versioned prompts so output does not drift silently

Our process

Four steps from brief to reviewed output

Quality is defined before generation starts.

  1. 01

    Define the output

    What is generated (text, images, summaries), for whom, and what good looks like.

  2. 02

    Choose & compare models

    Candidates tried on your own examples for quality, speed and cost.

  3. 03

    Build the pipeline

    Prompts, templates, brand rules and review steps around the model.

  4. 04

    Review, release & monitor

    People review where it matters, then quality and spend are monitored.

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.

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.

Prompt Engineering

Better prompts, better results.

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 encode your style, terms and examples into the prompts and checks, and review samples with you before launch.

Not without checks. We add review steps and rules for the cases that matter, and we say which outputs should always have a person in the loop.

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 one kind of content

Two weeks, your brief, working output and a clear view of quality and cost.

Start the POC