Katalyst AI Lab
Enterprise AI
as a Service
20+ AI/ML engineers who build, train, and ship, from first model to production deployment.
Katalyst AI Lab is the AI engineering division of Katalyst Software Services Limited. We take on the full build: training, fine-tuning, and deploying custom AI systems for enterprises across BFSI, legal, healthcare, and manufacturing. RAG knowledge assistants, domain-specific LLMs, computer vision pipelines, MLOps infrastructure, everything is built to your specs, transferred to your ownership, and documented for your team to run.
20+
AI / ML Engineers
4
Client AI Products Shipped
10+
Industries Served
8+
Years Enterprise Delivery
Explore AI Lab
Your Gateway to Enterprise AI
From agentic systems and RAG to fine-tuning, MLOps, and production deployment — pick a path below.
Agentic AI & RAG
Build autonomous AI agents that reason, retrieve, and act. Multi-agent pipelines and RAG systems on any foundation model.
Explore →LLM Fine-Tuning
LoRA, QLoRA, PEFT, and full fine-tuning on your data.
Explore →MLOps
CI/CD for models, drift monitoring, cloud deployment.
Explore →Vision & NLP
OCR, clinical NLP, object detection, defect inspection.
Explore →AI Safety
Red-teaming, eval harnesses, guardrails before deploy.
Explore →Industries
Purpose-built AI for BFSI, healthcare, legal, manufacturing, and more — designed around your compliance requirements.
Explore →Client Products
Fintly, ProcBay, ProcXO, and ExpertsHub — four live AI products we built end-to-end for paying clients.
Explore →Hire Engineers
Dedicated AI/ML engineers on your team.
Explore →
What We Build
AI Capabilities
Six specialisations. One team. End-to-end delivery from PoC to production.
Agentic AI & RAG Systems
We build agents that reason over your data, call your tools, and complete tasks end-to-end. Multi-agent pipelines and RAG systems on any foundation model, connected to your existing stack.
Explore →LLM Fine-Tuning & Model Training
Your proprietary data trained into the model, not appended to a prompt. We use LoRA, QLoRA, PEFT, and full fine-tuning to get domain-specific accuracy at lower inference cost than generic APIs.
Explore →MLOps & Model Lifecycle
CI/CD for models, automated retraining triggers, drift monitoring, and cloud-agnostic deployment on AWS, GCP, or Azure. Your model stays accurate after it ships.
Explore →Computer Vision & NLP
Document OCR, clinical NLP, real-time object detection, we build perception models for the specific inputs your operations actually produce.
Explore →AI Safety & Evaluation
Red-teaming, eval harnesses, adversarial testing, bias audits, and alignment benchmarking, before your model goes anywhere near production.
Explore →Vertical AI Solutions
Purpose-built AI for BFSI, healthcare, legal, and manufacturing designed around your compliance requirements, data structures, and workflows.
Explore →
How We Engage
From Brief to Production
A proven four-phase delivery model with clear milestones, benchmarked PoCs, and fixed-price options before you commit further.
Weeks 1–2
Discovery & Scoping
We audit your data, assess AI readiness, shortlist use cases, and recommend an architecture. You receive a written proposal with fixed-price options before any development spend is committed.
Weeks 3–6
Proof of Concept
A working prototype on your actual data. We benchmark it against off-the-shelf alternatives and deliver ROI projections. You decide whether to proceed.
Months 2–4
Build & Fine-Tune
Full system development: model training or fine-tuning, RAG pipeline construction, integration with your existing stack, and a test suite covering your edge cases.
Month 4+
Deploy & Operate
Production deployment, MLOps instrumentation, monitoring dashboards, and formal handover with full documentation. Ongoing retainer available.
Verticals
Industries We Serve
BFSI
Credit risk modelling · Fraud detection · Regulatory document intelligence · Customer churn prediction
Healthcare & Life Sciences
Clinical NLP · Medical imaging analysis · Prior auth automation · Patient journey AI
Legal
Contract review & extraction · Due diligence acceleration · E-discovery · Regulatory monitoring
Manufacturing
Predictive maintenance · Visual quality inspection · Supply chain forecasting · Process optimisation
Publishing & Research (STM)
AI-assisted content structuring · Semantic tagging · Reference linking · Metadata generation
E-Commerce & Retail
Recommendation engines · Demand forecasting · Returns prediction · Personalisation at scale
Why Katalyst
A Different Kind of AI Partner
We are the only AI services team that can show you four production AI products delivered for clients before you've signed a contract.
01
We Ship.
Four AI products: Fintly, ProcBay, ProcXO, and ExpertsHub , built end-to-end by our team and live in production today. Real clients, real deadlines, real briefs. We ship AI systems.
02
You Own Everything.
Model weights, training code, data pipelines, and documentation are transferred to you at project close. No vendor lock-in. No black-box dependencies. No recurring licence for what we built.
03
Enterprise Delivery Standards.
Katalyst Software Services is part of an 800+ person group operating across India, UK, US, and the Philippines, serving global publishers including Taylor & Francis and Oxford University Press.
04
Data Privacy First.
NDAs before day one. Isolated compute environments. Training data never leaves your approved infrastructure. We operate within your AWS, GCP, or Azure tenant throughout the engagement.
05
Vertical Specialists On Staff.
BFSI, healthcare, and legal domain experts are embedded in our AI team. Your models are trained by engineers who understand your compliance constraints, not brought in as consultants after the fact.
Technology
Tools & Frameworks
The platforms and frameworks our engineers use across training, agents, MLOps, vision, and cloud deployment.
OpenAI
GPT-4o
GPT-4o
Anthropic Claude 3.5/3 Opus
Meta
LLaMA 3
LLaMA 3
Mistral
7B/8x7B
7B/8x7B
Google Gemini
1.5 Pro
1.5 Pro
Microsoft
Phi-3
Phi-3
LoRA
QLoRA
PEFT
Hugging Face Transformers
Axolotl
DeepSpeed
LitGPT
DPO
LangChain
LangGraph
LlamaIndex
CrewAI
Pinecone
Weaviate
Chroma
PG Vector
Qdrant
MLflow
Weights & Biases (W&B)
Kubeflow
Prefect
BentoML
Seldon Core
Ray Serve
Evidently AI
YOLO v8/v9
Detectron2
SAM
EfficientNet
OpenCV
Roboflow
Spacy
NTLK
Hugging Face Transformers
Whisper
Tesseract
AWS SageMaker
GCP Vertex AI
Azure ML
Lambda Labs GPU Cloud
Label Studio
Scale AI API
Prodigy
Select a category to explore our tooling
Client Work
AI Products We've Shipped for Clients
The clearest proof of delivery capability is a live product built for a paying client. These four are live, serve real users, and were delivered end-to-end by our team.
Fintech / BFSI
Fintly · fintly.co
NLP on financial data, predictive analytics, automated reporting, anomaly detection
View live product →
Procurement Marketplace
ProcBay · procbay.com
Embedding-based vendor matching, demand signal processing, spend analytics
View live product →
Procurement AI Copilot
ProcXO · procxo.ai
Fine-tuned LLMs on procurement datasets, contract analysis, RFP generation, risk detection
View live product →
Talent Marketplace
ExpertsHub · expertshub.ai
Custom embedding models for expert-to-project matching, AI brief writing, proposal scoring
View live product →
FAQ
Questions
What types of AI projects does Katalyst AI Lab take on?
Everything from a focused proof-of-concept experiment to a full production AI system. Common engagements: domain-specific LLM fine-tuning, RAG knowledge assistants, multi-agent pipelines, computer vision applications, clinical NLP, and end-to-end MLOps infrastructure.
How is our data protected when working with your offshore team?
NDAs are signed before any data is shared. Your training data never leaves your approved cloud infrastructure. We operate within your AWS, GCP, or Azure environment, or provision isolated compute on your behalf. All model weights, code, and data pipelines are formally transferred to you at project close.
Do you work with open-source models or only proprietary APIs?
Both. The right choice depends on your latency requirements, data privacy constraints, and budget. GPT-4o via API is sometimes the right call. A fine-tuned 7B open-source model running on your own servers is sometimes better. We recommend what genuinely fits your use case.
What is the difference between fine-tuning and RAG?
Fine-tuning permanently updates model weights using your domain data, so the knowledge becomes part of the model itself. RAG connects a model to an external retrieval system at query time for live or frequently updated information. Both serve distinct needs, and many robust production systems use both together.
How long does a typical engagement take from start to production?
Discovery and scoping: 1–2 weeks. Proof of concept: 3–6 weeks. Full production build including integration, testing, and deployment: 3–5 months depending on data readiness and system complexity.
What does a typical engagement cost?
Proof-of-concept engagements typically range from $15,000 to $40,000 USD depending on scope. Full builds vary significantly. After the discovery session we provide a fixed-scope estimate before any development spend is committed.
Get Started
Ready to Build Something That Actually Works?
Book a 30-minute no-commitment AI strategy call, or send us a project brief and we'll respond within 24 hours.