AI Solutions

From clever demo to enterprise-grade AI.

We help BFSI, healthcare, retail, and SaaS leaders translate GenAI ambition into reliable products — with the guardrails, observability, and governance their security and legal teams actually approve.

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40+

AI engagements shipped

LLM-powered products in prod

98.6%

Avg. eval pass rate

60 days

Avg. proof-of-value timeline

The practice

We've watched enough AI POCs die quietly. We design backwards from the production line.

Most teams can wire up an LLM in a weekend. The hard part — the part that decides whether your AI ever sees a real customer — is the next 90 days: retrieval that doesn't hallucinate, evals that catch regressions, a cost model that survives scale, and a compliance posture your CISO will sign.

Our AI practice is built around that production reality. Every engagement is led by a senior engineer who has shipped AI to paying users before, paired with a domain analyst who understands your industry's language and edge cases.

We work in tight loops: a measurable success metric is defined in week one, instrumented in week two, and reported on every Friday. No magic. No theatre. Just AI that quietly earns its keep.

Technology Expertise

Technologies Your Teams Already Trust.

We build teams around modern engineering ecosystems ensuring every developer is aligned with your stack, workflows, and delivery standards.

LLM Engineers

GenAI & RAG

LangChainOpenAIAnthropic

RAG Specialists

Retrieval

PineconeWeaviatepgvector

Prompt Engineers

Prompt Design

DSPyGuidanceLMQL

AI Safety Eng.

Guardrails

EvalsPresidioRebuff

Capabilities

The full surface area.

Everything we offer within this practice, delivered by senior practitioners — not handed to juniors after the contract is signed.

GenAI strategy & opportunity sizing

A 2-week diagnostic: where AI moves the metric, where it's a distraction, and what the realistic ROI window looks like.

RAG & knowledge systems

Production-grade retrieval over your docs, tickets, code, and structured data — with citations, fallbacks, and cost ceilings.

Agentic workflows

Multi-step agents that draft, review, and act — with human-in-the-loop checkpoints designed by your compliance team.

Fine-tuning & distillation

When prompt engineering hits the wall: SFT, DPO, and distilled open models that cut latency and lock in your voice.

MLOps, evals & guardrails

LLM observability, regression evals, prompt versioning, PII scrubbing, and red-team harnesses baked into your CI.

Computer vision & document AI

OCR, layout-aware extraction, and visual QA pipelines for insurance, logistics, manufacturing, and healthcare.

Methodology

A repeatable path from idea to outcome.

Diagnose

We map your workflows, data, and risk appetite — then pick the 1–2 use cases where AI moves a number, not vibes.

Prototype

A live prototype on your data in 3–4 weeks, paired with an evaluation harness and a cost dashboard from day one.

Productionise

Hardening for scale, observability, security review, and a clean integration into your existing product surface.

Operate

Ongoing evals, drift monitoring, model upgrades, and a quarterly review focused on the business metric we agreed on.

Engagement models

Commercial shapes that fit how you actually work.

Discovery sprint

Fixed-price, 2 weeks. A senior AI engineer plus an analyst, working alongside your team to size opportunities and pick a beachhead use case.

Working sessions with your domain experts
Architecture sketch and cost model
Prioritised opportunity backlog
Risk and compliance pre-read

POV to production

Time-and-materials, 8–16 weeks. A pod of 3–5 senior engineers takes the chosen use case from prototype to a production pilot.

Live system on real data
Eval harness and CI integration
Security review pack for your CISO
Documented handover or co-managed run

Embedded AI squad

Monthly retainer. A long-running AI team that becomes a part of your product org and owns the AI roadmap end-to-end.

Dedicated senior tech lead
Quarterly OKR planning with your PM
Joint on-call rotation
Predictable monthly burn

Related case studies

Proof from similar work.

A few relevant engagements that match this practice area.

Global Recruitment & Talent Development Organization

Human Resources & Career Development

Case study

Global Recruitment & Talent Development Organization

Challenge — AI-powered interview simulation platform improved candidate success rates by 78%.

What we did — Built an AI interview preparation platform with GPT-based simulations, real-time speech analytics, and smart proctoring. Delivers role-specific training and performance scoring while eliminating fraudulent hiring practices.

78%

Increase in interview success rates

85%

Improvement in speech confidence

70%

Cost savings

Local GPT for Secure Financial Operations

Financial Services & Banking

Case study

Local GPT for Secure Financial Operations

Challenge — Fully on-premises AI platform achieved 300%+ ROI while maintaining zero-breach security.

What we did — Implemented a fully on-premises AI platform with offline LLMs, secure document intelligence, SQL-based analytics, and workflow automation. Strict regulatory requirements prevented external data sharing.

85%

Faster document processing

95%

Data retrieval accuracy

300%+

First-year ROI

Voices

What the people writing the cheques say.

"Pure was the only partner who started by asking us how we'd measure success — not by showing slides of someone else's chatbot."

VSVikram SubramanianChief Digital Officer · Top-5 Indian Bank

"We had three vendors attempt the medical summarisation problem. Pure was the only team that took the safety constraints seriously from week one."

ARDr. Anika RaoVP Clinical Products · Lumenpath Health

"Their eval harness alone changed how our internal ML team thinks about quality. That's value beyond the engagement itself."

KNKarthik NairHead of Data Science · Northwind SaaS

Why trust Pure Technology

Six reasons enterprise teams renew with us, year after year.

Trust isn't a logo wall — it's the operating rigour you feel from the first call. Here's what backs ours.

Compliance you can audit

SOC 2 Type II aligned process, ISO 27001 controls, DPDP-ready data handling, and signed MSAs that don't read like a trap.

Senior by default

9 years average experience on every squad. The engineers you meet in the pitch are the engineers who ship — no bait-and-switch.

Top 3% talent bar

Every engineer clears a 4-stage technical bar modelled on FAANG-style hiring. Only ~3% of applicants make our bench.

Predictable cadence

Two-week ship cycles, a Friday demo, and a written changelog. You always know what's done, what's next, and what's at risk.

Long-term partnership

Average client tenure is 3.4 years. We design for year two of a relationship, not the first invoice — and it shows in the work.

Outcomes, measured

Every engagement starts with a defined success metric and a shared dashboard. We report on outcomes, not just hours burned.

Certifications & registrationsISO/IEC 27001SOC 2 Type II alignedDPDP compliantGDPR readyMSME registeredSTPI registered

FAQ

The questions enterprise buyers actually ask.

Both. We're model-agnostic — OpenAI, Anthropic, Google, Mistral, Llama-family, and self-hosted open models. We benchmark against your data and pick the option that wins on quality, latency, and cost for your specific use case.

Keep exploring

We rarely do just one of these.

Most engagements eventually pull in a sibling practice — talent into AI, AI into product, product into talent.

IT Staffing Product Engineering

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Connect with Our Team

For HR & Carrers+91 73875 81577 For Support+91 83298 49726 For AI Project+91 99701 11283 For Hire Resource+91 73854 55380

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