AI Integration

AI Features That Deliver Real Outcomes

We embed LLMs, intelligent automation and predictive capabilities into your product — engineered for production, measured by results.

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What's Included

AI features that work in production, not just demos

Most AI projects fail between prototype and production. We bridge that gap — handling prompt engineering, RAG architecture, latency optimisation, cost management and monitoring so your AI feature ships and keeps working reliably at scale.

AI Strategy & Use Case Scoping

We identify which of your workflows genuinely benefit from AI versus which should stay deterministic. A focused use case with measurable outcomes beats a sprawling AI project every time.

LLM Integration (OpenAI, Anthropic, Llama)

API integrations with OpenAI GPT-4o, Anthropic Claude or open-source models (Llama 3, Mistral) — chosen based on your latency, cost and data-privacy requirements.

RAG Architecture & Vector Search

Retrieval-Augmented Generation systems that ground LLM responses in your proprietary documents, product catalogues or knowledge bases — reducing hallucinations and enabling domain-specific accuracy.

AI Agents & Workflow Automation

Autonomous agents built with LangChain or custom orchestration that can retrieve data, call APIs and take multi-step actions across your connected business systems.

MLOps & Production Monitoring

Latency tracking, cost-per-request monitoring, output quality evaluation, model version management and automated alerts — so you know when your AI feature degrades before your users do.

Privacy-First AI Architecture

For regulated industries or sensitive data, we deploy models on-premise or in your private cloud — your data never leaves your infrastructure and no third-party model provider sees it.

Deliverables

Production-ready AI feature or service deployed to your environment
API endpoint documentation with request/response examples
Latency and cost benchmark report
Monitoring dashboard (token usage, cost, error rate, latency)
Prompt library and model evaluation framework
Data privacy impact assessment (for sensitive use cases)
Team handover and training session
30-day post-launch support

Who this is for

SaaS products adding AI features (chatbots, summarisation, classification)
Enterprises automating internal workflows using their proprietary documents
Companies building AI-native products from the ground up
Teams who built an AI prototype but can't get it production-ready

Technologies

OpenAI GPT-4o Anthropic Claude Llama 3 Mistral LangChain LlamaIndex Pinecone pgvector FastAPI Python Docker GCP Vertex AI

Process

A transparent path from idea to launch

Six clear stages, weekly demos and one shared source of truth — so you always know where things stand.

Discovery

Workshops to uncover goals, users and constraints.

Planning

Roadmap, architecture decisions and clear estimates.

Design

Wireframes and high-fidelity UI validated with users.

Development

Agile sprints with weekly demos and code reviews.

Testing

Automated QA, security audits and performance tuning.

Launch

Smooth deployment, monitoring and ongoing support.

Testimonials

What partners say

A few words from the founders and product leaders we've shipped alongside.

Pragyasuite replaced three vendors with one senior team. They shipped our new platform in 14 weeks and it has scaled to 5x the traffic without a hiccup.

Anika Verma VP Product, Northwind Finance

Rare combination of strong engineering and genuine product thinking. They pushed back when we needed it, and the architecture choices have aged really well.

Daniel Hoffmann CTO, Cargopath Logistics

They modernized a decade-old codebase with zero downtime. Weekly demos kept everyone aligned and the rollout to 12 hospitals went off without surprises.

Folake Adeyemi Head of Engineering, CareSync Health

FAQ

Frequently asked questions

Straight answers to the questions we hear most from clients and prospects.

Which AI and ML technologies do you use?

We work with OpenAI, Anthropic and open-source LLMs (Llama, Mistral), as well as traditional ML frameworks (scikit-learn, PyTorch, TensorFlow). We select the right tool based on your latency, cost and data-privacy requirements.

Can you build AI features on our existing platform?

Yes. We specialize in embedding AI capabilities into existing products via API integrations, internal microservices or SDK wrappers — without requiring a full rebuild.

How do you handle data privacy when using AI?

We architect AI pipelines with data minimization, anonymization and strict access controls. For regulated industries we can deploy models on-premise or in private cloud environments so your data never leaves your infrastructure.

Ready to Build Your Next Software Solution?

Tell us about your project. We'll come back within one business day with a clear next step — no pressure, no jargon.

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Locations

We serve businesses across India

Our team works remotely and on-site. Browse our AI Software Solutions & Integration services by city.