Enterprise AI

Every engagement reaches production.

Production AI for Fortune 500 clients across four industries. No demos.

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Our Process

Assessment to production in 90 days

01

Assessment

Map data, infrastructure, and the problem worth solving

02

Architecture

Designed for your stack, not a whitepaper

03

Build

Models, pipelines, integrations

04

Deploy

Monitoring, guardrails, rollback plan

05

Measure

Accuracy, latency, cost, business impact

06

Scale

Expand across teams and geographies

Results

Production deployments. Measurable returns.

Financial Services · UAE

Mashreq Bank

Document intelligence for account onboarding and transactions. AI Guru worked alongside Mashreq's team to lift extraction accuracy across hundreds of fields and dozens of document types.

Manufacturing

JMC Paper Tech

MillMind — the AI behind JMC's production intelligence: real-time monitoring, predictive maintenance, and energy optimization, live at 1,000+ TPD facilities.

Insurance (P&C)

GenAIRate

SnapLine — core property & casualty functionality that turns messy broker submissions (email, PDF, ACORD, Excel) into structured, quote-ready data for Lloyd's, the London Market, and MGAs.

Financial Advisory · UK

Money A&E

Real-time audio translation for advisor–client meetings — the advisor speaks English, the client hears Spanish, instantly and both ways, with no human interpreter in the room.

Healthcare & Life Sciences

Kernshell

A targeted AI solution supporting clinical-study workflows in a regulated healthcare environment.

100,000+
Professionals Trained
20
Products in Production
72
NPS Score
20+
Deployed in 20+ Countries

Capabilities

What we deploy

RAG systems & knowledge retrieval
Agentic workflows & orchestration
Fine-tuned & custom LLMs
Enterprise API integrations
Multi-model architectures
AI evaluation & observability

Technical Depth

Platforms & models

AWSAzureGCPCerebrasGroqNVIDIAGPT-4o/5ClaudeLlamaMistral

Industries

Four industries. Deep operational knowledge.

Financial Services

Manufacturing

Media & Entertainment

Healthcare

Case Studies

Proof in production

Financial Services

“AI governance framework board-approved within 6 weeks. Zero regulatory findings in subsequent audit.”

— Leading Indian Private Bank

Manufacturing

“60-80% of mill staff using AI platform daily within 90 days. Equipment lookup reduced from 30-60 minutes to under 1 minute.”

— JMC Paper Tech (MillMind deployment)

IT Services

“2,000+ engineers trained across 4 delivery centers in 8 weeks. 35% increase in AI-related project wins next quarter.”

— Major IT Services Company

FAQ

Frequently asked questions

Do you only advise, or do you actually build the AI?

We build and deploy. Every engagement is designed to reach production — models, pipelines, integrations, monitoring, and guardrails — not slide decks or proofs-of-concept that never ship.

How long does a typical engagement take to reach production?

Our process runs from assessment to production in about 90 days: assessment, architecture, build, deploy, measure, and scale. Timelines vary with data readiness and integration complexity, but shipping to production — not a demo — is the goal from day one.

Which industries and platforms do you work across?

We deploy production AI for Fortune 500 clients across financial services, manufacturing, media & entertainment, and healthcare, on AWS, Azure, GCP, and specialized stacks (Cerebras, Groq, NVIDIA), with GPT, Claude, Llama, and Mistral models.

What kinds of AI systems do you deploy?

RAG systems and knowledge retrieval, agentic workflows and orchestration, fine-tuned and custom LLMs, enterprise API integrations, multi-model architectures, and AI evaluation and observability.

How is AI Guru different from a typical consultancy?

We are a venture studio that ships production AI and operates 20 of our own products, so engagements draw on real deployment experience rather than theory. We will also tell you when AI is not the right fit before putting anything into production.

Bring your hardest AI problem.

We'll tell you if AI is the right fit — then put it in production.

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