Transform Your Business with Enterprise AI
Proven AI Solutions | 70% Cost Reduction | 5x ROI | 95% Accuracy
schedule Average Time to ROI: 12 Months | psychology Specialized in RAG, Agentic AI, LLM Fine-Tuning
What the hjLabs.in AI/ML team does
hjLabs.in is a Gandhinagar-based AI/ML consultancy that ships production-grade machine learning systems for enterprises — not slide-deck strategies, not throw-away PoCs, but live systems that handle real workloads and survive your real users. Since 2017 we have delivered 50+ production AI deployments to teams across 12 countries — US, UK, Canada, Australia, Germany, Netherlands, Switzerland, Sweden, UAE, Saudi Arabia, Singapore and India — covering our full catalog of AI/ML services for manufacturers, including RAG systems, LLM fine-tuning, agentic AI development, computer vision and MLOps & deployment.
We work with mid-market to enterprise teams that have either tried a vendor and got burned, or built something internally that does not scale. Our delivery model is senior-only, async-first, fixed-price-per-milestone — three things that fix the three biggest pains we hear about ML consulting: junior-heavy teams, T&M scope creep and hourly billing surprises. Read on for our five service pillars in depth, the seven industries we serve, our four-phase engagement model, and the honest pitch for why India offshore beats both local and SE Asia delivery.
Our five AI/ML service pillars
Each pillar is a fully-productised offering with its own scoping playbook, reference architecture, and case studies. Click through for the full service page.
📚 1. RAG System Development
Retrieval-Augmented Generation is the fastest path from "we have documents" to "we have a smart assistant". We build production RAG over your contracts, manuals, support tickets, research papers or knowledge bases — typical scale runs from 500 PDFs to 5 million chunks. Stack: LangChain or LlamaIndex orchestration, Pinecone/Weaviate/pgvector for embeddings, OpenAI/Anthropic/local Llama for generation, and a custom evaluation harness so you know when answers regress. We ship with hybrid search, re-ranking, citation tracking and PII redaction baked in. Average outcome: 75% faster knowledge retrieval, 94% answer accuracy. Full RAG service page →
🎯 2. LLM Fine-Tuning
When prompt engineering hits a ceiling and you need a model that genuinely understands your domain vocabulary, fine-tuning is the answer. We run LoRA and QLoRA for parameter-efficient adaptation on open models (Llama 3.1/3.3, Mistral, Qwen 2.5, Gemma 2, Phi-4) and full fine-tuning when domain shift is large. Includes synthetic data generation, instruction-tuning dataset prep (typical: 5K-50K examples), hyperparameter sweeps and rigorous eval against your task. Self-hosted deployment via vLLM or TGI cuts inference cost 70% below frontier API pricing at production scale, while custom training lifts task accuracy 30–50%. Full LLM fine-tuning service →
🤖 3. Agentic AI Development
Agentic AI is the leap from "LLM that answers questions" to "LLM that completes tasks". We build autonomous agents that plan multi-step workflows, call tools (your APIs, databases, third-party services), recover from errors, and produce auditable execution traces. Frameworks: LangGraph, CrewAI, AutoGen, OpenAI Assistants and custom orchestration where the off-the-shelf options break. Use cases we have shipped include customer-support auto-resolution, sales-research agents, invoice processing, contract review and developer copilots. Typical outcome: 80% workflow automation on routine tasks, freeing humans for exception handling. Includes guardrails, observability via LangSmith/Langfuse and human-in-the-loop checkpoints. Full agentic AI service →
👁️ 4. Computer Vision
Real-world CV — not Kaggle scoreboards. We ship defect detection on factory floors, OCR for back-office automation, video analytics for retail and logistics, medical-imaging classification, and quality-control inspection lines. Stack covers YOLO v8/v11 detection, SAM 2 segmentation, vision-language models (LLaVA, Qwen-VL, Gemini Vision) for open-vocabulary tasks, edge deployment on Jetson/Coral/ONNX runtime, and synthetic data generation when you have <500 labelled samples. Typical production accuracy: 95%+ on bounded inspection tasks; ROI: 60–70% inspection labour reduction. Includes integration with your factory PLC, ERP or video pipeline. Full computer vision service →
⚙️ 5. MLOps & Deployment
Every Bay-Area survey says the same thing: ~85% of ML models never reach production. We are the reason yours will. MLOps engagements deliver CI/CD pipelines for ML (GitHub Actions/GitLab CI), feature stores (Feast/Tecton), model registries (MLflow, Weights & Biases), drift detection and automated retraining triggers, A/B testing infrastructure, and SLA-grade serving on Kubernetes/Ray/Modal/AWS SageMaker. Includes observability dashboards (Grafana, Datadog), incident playbooks and runbooks. We typically take a model from "works in notebook" to production with monitoring in 4–8 weeks. Full MLOps service →
Industries we serve
We have shipped production AI/ML systems across seven primary verticals. Each industry page below covers the specific use-cases, reference architectures and case-study outcomes we have delivered.
How we work — 4-phase engagement model
The same delivery rhythm we have used for 50+ production projects. Predictable cadence, clear go/no-go gates, no surprises.
🔍 Discovery & Strategy
2–3 weeks. We map your data sources, define success metrics, run feasibility tests on sample data, draft a reference architecture and deliver a written go/no-go recommendation. You get a complete strategy doc whether or not we continue together. Typical cost: ₹2.5–6 lakh.
🛠️ Build & Iterate
4–12 weeks. We ship a working artefact by week 3 and iterate weekly with a live demo every Friday. You get a Slack channel with our engineers, a project board you can see, and code in your GitHub from day 1. No dark-room consulting.
🚀 Pilot & Validate
2–4 weeks. Limited-audience rollout — a subset of users, a single business unit, a controlled traffic slice. We instrument everything, track real-world performance against the success metrics defined in Phase 1, and tune until acceptance criteria are green.
📈 Scale & Handoff
2–4 weeks + ongoing. Full production rollout, runbook docs, on-call rotation if you need it, and team training so your engineers own the system on day 91. Optional Retainer (₹3.3–10 lakh/month) for continued evaluation, drift watching and model updates.
Why offshore India AI/ML — the honest pitch
The standard arguments for offshore India delivery — "cheaper" and "we speak English" — are tired and partially wrong. The actual argument in 2026 is sharper. One: Indian senior ML engineers cost 3.5–6× less than Bay-Area equivalents, which lets us put a 100% senior team on your project at a price US firms charge for a 50/50 senior-junior mix. That is the difference between code review by someone who has shipped 8 production models and someone who finished a bootcamp last quarter. Two: IST overlaps with EU and APAC business hours, so async-first delivery feels natural — your standup at 9am London is our 2:30pm Gandhinagar with the full team on. Three: 8 years of cross-border delivery to teams in the US, UK, UAE, Germany, Singapore and Australia means the communication overhead — proposals, kick-offs, stand-ups, async written updates, demo cadence — is solved.
We win against SE Asia (Vietnam, Philippines, Indonesia) because we ship senior-only — most SE Asia consultancies are junior-heavy and charge less but deliver less. We win against the US/UK because the math is unbeatable for the same staff mix. Read the full breakdown in our India offshore AI/ML consulting guide — it covers win/loss data, time-zone playbooks, IP and data residency, and the SOC 2 / GDPR delivery patterns we use for regulated industries.
Frequently asked questions
Five questions we hear on almost every scoping call.
Why hjLabs.in is Your Best Choice
Trusted by enterprise teams across 12 countries, we deliver production-ready machine learning consulting and AI ML consulting that drives measurable ROI. Here's what makes us different:
Production-Ready
We deploy to production, not just POCs
Proven Track Record
50+ systems live in production
Fast Implementation
Average project: 8-12 weeks
Ongoing Support
95% client retention rate
Real Results. Real Impact.
Quantifiable outcomes achieved by our clients
Trusted Across Industries
Real implementations. Real clients. Real success.
Healthcare
RAG System
E-commerce
AI Recommendations
Financial Services
Fraud Detection
Manufacturing
Predictive Maintenance
AI Consulting Services That Drive Results
From AI strategy consulting to production deployment — cutting-edge solutions for 2025. Explore our core offerings: Agentic AI Development, RAG System Development, LLM Fine-Tuning, and MLOps & Deployment.
AI Agentic Systems
Autonomous AI agents that handle complex workflows end-to-end
RAG Systems
Transform documents into intelligent, searchable knowledge bases
LLM Fine-Tuning
Custom AI models trained on your specific domain and data
MLOps & Deployment
Production-grade infrastructure for scaling AI systems
What Our Clients Say
Real feedback. Real impact.
"Fantastic AI engineer with pragmatic business and technical skills. Great to work with. An asset to any team."
Managed Hemang directly
"The RAG system transformed how our doctors access knowledge. Research time dropped from 5 hours to 75 minutes per week, and accuracy is at 94%. Direct impact on patient care."
Hospital Network
"The AI recommendation engine didn't just increase sales - it transformed our customer experience. $290K additional annual revenue and 32% conversion boost."
E-commerce Platform
"Predictive maintenance system reduced downtime by 68% and saved $215K annually. From reactive to proactive. ROI clear within 6 months."
Manufacturing
Industry-Leading Technology
We work with the best AI platforms and infrastructure
AI Platforms
Cloud Infrastructure
Frameworks & Tools
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email [email protected] | phone +91 701 652 5813