AI Engineering · Hyderabad → The World

We build the AI that survives production.

Demos are easy. Systems are hard. QuantPi engineers the full distance — evals, infrastructure, guardrails, governance — for enterprises that need AI to hold up under real traffic, real auditors, and real unit economics.

deploy · pipeline ingest evals deploy ✓ eval suite passed — 412/412 ✓ faithfulness 0.94 · p95 380ms # canary 5% → 50% → 100% GROUNDEDNESS / RELEASE ▲ 0.94 this release COST / REQUEST $0.0041 ▼ 68% vs baseline
50+AI products shipped
98%client retention
3.2×average ROI delivered
12+industries served
SYS/01What we build

Services

Nine disciplines, one standard: if it can't be measured, monitored, and handed over, it isn't done.

AI Product Development

Discovery to launch: eval harnesses, serving infrastructure, and the unglamorous 80% that makes AI dependable.

read the spec →

LLM Integration & RAG

Retrieval systems with measured faithfulness — grounded answers that cite sources or decline to guess.

read the spec →

ML Engineering & MLOps

Feature pipelines, deployment automation, and drift monitoring. The 95% of ML that isn't the model.

read the spec →

AI Strategy Consulting

Roadmaps written by engineers — every recommendation carries an architecture, a cost model, and a kill criterion.

read the spec →

Cloud Infrastructure for AI

GPU orchestration, landing zones, and hybrid stacks on Azure, AWS, GCP — or fully inside your network.

read the spec →

Document Intelligence

OCR, layout-aware extraction, and semantic search that turn document piles into queryable, auditable data.

read the spec →

Responsible AI & Governance

EU AI Act, GxP, model risk — compliance engineered into the stack, evidence generated by the system.

read the spec →

GCC as a Service

AI-first capability centers in Hyderabad — advisory, build, or build-operate-transfer.

read the spec →

Transformation Consulting

Operating models proven by delivery: we ship a lighthouse, then systematize what worked.

read the spec →
SYS/02Where we build it

Industries

Domain constraints aren't obstacles to the engineering — they are the engineering.

Healthcare & Life Sciences

GxP-validated AI with audit trails an inspector can follow.

explore →

Financial Services

Models that pass second-line review — explainable, monitored, fair-lending tested.

explore →

Manufacturing

Vision and predictive systems engineered for operator trust and edge networks.

explore →

Retail & E-commerce

Search, pricing, and forecasting measured the way retail respects: on the P&L.

explore →

Supply Chain & Logistics

Demand sensing and document automation that compress the cash cycle.

explore →

Enterprise SaaS

AI-native features with per-tenant cost control and provable isolation.

explore →
SYS/03What we productized

Products

Patterns we shipped enough times to turn into platforms.

AI-DMS

Document intelligence, deployable anywhere

OCR, classification, extraction, semantic search, and a RAG copilot over your documents — on-premises first, cloud-pluggable by design. Built for organizations whose documents can't leave the building.

see the platform →
deploy: air-gapped · cloud · hybrid
QEXIM

Trade intelligence for import/export

Compliance documentation, customs automation, shipment tracking, and quote generation for global trade operations — the paperwork layer of trade, automated.

see the platform →
domain: global trade · 40+ doc formats
SYS/04Why teams pick us

The operating principles

Engineers, end to end

No handoff between the people who sell, design, and build. The architect on the first call writes code on the project.

Evidence over opinion

Eval suites before features, baselines before models, measurement before claims. Every promise is testable.

Full IP transfer, zero lock-in

Code, infrastructure, evals, runbooks — all yours. We compete on the next project, not on captivity.

Regulated-grade discipline

GxP, financial MRM, EU AI Act — we build for the audit you'll face, in industries where 'move fast' is a finding.

SYS/05Field notes

From the engineering blog

RAG

RAG vs fine-tuning vs prompt engineering

A decision framework drawn from production systems — when each works, when each quietly fails.

read →
Cost

How we cut ML inference costs 68%

Quantization, batching, and right-sizing — the engineering ledger of a real cost-reduction project.

read →
Agents

Multi-agent systems in production

What survives contact with real users when you orchestrate LLM agents — and what doesn't.

read →
SYS/06Common questions

FAQ

What does QuantPi.ai do?
We're a production-grade AI engineering company in Hyderabad. We build AI products, LLM/RAG systems, ML pipelines and AI infrastructure for US, European and Indian enterprises — and we design, build and operate AI-first Global Capability Centers.
How is QuantPi different from other AI consultancies?
Our strategists are the engineers who build. Every claim is backed by eval suites and measurement, not slideware. And clients receive full IP transfer with zero lock-in — we compete on the next project, not on captivity.
Do you work with startups or only enterprises?
Both. Startups typically engage us for product engineering velocity; enterprises for regulated-grade delivery and GCC builds. The common thread is needing AI that works in production, not in a pitch.
How do we start?
Book a 30-minute call. You'll get a candid read on feasibility and approach — and if there's a fit, a short framing engagement with defined deliverables before any large commitment.

Ship AI that earns its place in production.

Tell us what you're building. We'll tell you, candidly, how we'd build it — architecture, timeline, and cost.

Average first response: under 24 hours · straight engineering answers, no pitch theatre