AI and data teams that ship to production.
Data engineering, data science, machine learning, generative and agentic AI, and AI automation, built by engineers in India and run with the discipline that keeps models working after launch.
Where demand in India is heading
64%
of new GCC roles in India in 2026 need AI, data science or intelligent-automation skills, up from 11% in 2021
30.3%
of GCC tech hiring demand is now AI, data and cybersecurity, even as overall demand dipped
21.1%
average pay rise for AI/ML roles at India GCCs in FY26, against 9.8% overall
58%
of India GCCs are investing in agentic AI; 83% in generative AI
What we build
Data engineering
Batch and streaming pipelines, lakehouse and warehouse models, data quality checks and monitoring, so analytics and AI run on data people trust.
- Pipelines and ELT
- Streaming
- Lakehouse
- Data quality
- Observability
Data science and machine learning
Forecasting, classification, anomaly detection and recommendation models, from first experiment to a model that is monitored in production.
- Feature engineering
- Forecasting
- Anomaly detection
- Model evaluation
Generative and agentic AI
LLM applications grounded in your data with retrieval, and agents that complete multi-step tasks with tools, guardrails and human approval where it matters.
- RAG and vector search
- Agents and tool use
- Prompt and LLM evaluation
- Guardrails
AI automation
Intelligent automation that pairs workflow tools and RPA with LLMs to take repetitive document, email and back-office work off people’s desks.
- Document AI
- Workflow automation
- RPA with LLMs
- Human-in-the-loop
MLOps and LLMOps
Versioned data and models, CI/CD for ML, cost and latency monitoring, and drift alerts, so models keep working after launch.
- Model registry
- CI/CD for ML
- Monitoring and drift
- Cost control
Data and AI governance
Access control, lineage, retention and AI risk reviews that line up with India’s DPDP Act and your own policies.
- Lineage and catalog
- Privacy by design
- AI risk review
- DPDP readiness
The skills we hire and train for
The newer skills are the hardest to find. We recruit for them directly and build them in graduates through our university training program.
- LLM application engineering
- Agent orchestration
- Retrieval-augmented generation
- LLM evaluation and red-teaming
- Vector databases
- Lakehouse platforms
- Real-time streaming
- MLOps and LLMOps
- Cloud AI services
- Data governance
- AI security
- Analytics engineering
Data work in production
For Neutrinos we designed and built a cloud data monitoring and anomaly-tracking console for enterprise banking and big-data teams.
Read the case study
Three ways to work with us on AI and data
Many clients start with a pilot or a few engineers, grow it into a dedicated team, and then into their own centre in India.
Build with us
A small cross-functional team takes an AI or data product from pilot to production, starting with our AI pilot program.
Start a pilotExtend your team
Data engineers, ML engineers and data scientists join your team and work in your tools and rituals.
Add AI and data engineersAI and data centre in India
We build an AI and data capability centre for you under Build-Operate-Transfer, then hand it over as your own.
How BOT works
Common questions
- What AI and data skills are most in demand in India?
- AI and data roles are the fastest-growing group in GCC hiring in India, and AI/ML roles saw the highest pay rises in FY26. Demand is strongest for generative and agentic AI, data engineering, MLOps and data governance skills.
- Can you build an AI centre of excellence inside our India GCC?
- Yes. We can staff and run an AI and data team as part of a Build-Operate-Transfer engagement, then transfer it to you with the rest of the centre, or set it up as a dedicated team that joins your existing GCC.
- How do you take an AI pilot to production?
- We agree a measurable outcome first, build the smallest version that proves it on real data, then add evaluation, monitoring and cost controls before scaling. Our AI pilot program ends with an MVP and a prioritized roadmap.
- How do you handle data privacy in AI projects?
- We design for least-privilege access, keep personal data out of prompts and logs where possible, and document processing roles so the system lines up with India’s DPDP Act and your own policies.