AI engineering consultancy
We build the AI systems that survive contact with production.
We take language models, agents and retrieval from prototype to systems that hold up under real traffic, real data and real accountability.
01 / Capabilities
What we are engineered to do
Applied LLM systems
Language model applications with grounded outputs, controlled cost and latency you can put in a contract.
Autonomous agents
Tool-using agents with real guardrails, clean human handoff and decisions you can trace after the fact.
Retrieval infrastructure
Ingestion, chunking, hybrid search and freshness pipelines built over your own corpus rather than a demo set.
Evaluation and reliability
Offline and online evaluation, regression suites and quality gates that stop a bad release before your users meet it.
Data and platform engineering
The pipelines, stores and serving layers underneath the model, sized for the load you actually have.
AI product engineering
The full product surface around the model, from interface and permissions through to billing and observability.
02 / Approach
A method, not a pitch deck
- 01
Diagnose
We start with your data, your constraints and your failure cases. Before any code, we agree on what good looks like and how it will be measured.
- 02
Prototype
A narrow working system against real data, not a slide. The goal is to find the hard parts early, while they are still cheap to change.
- 03
Harden
Evaluation suites, guardrails, cost and latency budgets, observability and rollback. This is the stage most AI projects skip and it is why they stall.
- 04
Transfer
Documentation, runbooks and paired delivery with your engineers, so the system keeps working after we step away.
03 / Engagements
Three ways to work with us
2 to 4 weeks
Discovery sprint
A fixed-scope engagement to establish whether an AI approach is viable, what it will cost to run and where the risk sits.
- Technical feasibility assessment
- Data and retrieval audit
- Evaluation plan and success criteria
- Costed delivery roadmap
3 to 9 months
Build partnership
We take end-to-end responsibility for delivering a system into production, working alongside your team throughout.
- Full system design and build
- Evaluation and reliability engineering
- Deployment and observability
- Knowledge transfer at handover
Ongoing
Embedded team
Senior engineers working inside your organisation to raise delivery throughput and establish AI engineering practice.
- Senior engineers in your workflow
- Architecture and technical review
- Practice and standards development
- Mentoring for your engineers
04 / Stack
Under the hood
We are not tied to a vendor. We pick per problem and we tell you why.
- Models
- Anthropic Claude, OpenAI, Google Gemini, open-weight models
- Orchestration
- Model Context Protocol, LangGraph, purpose-built event flows
- Retrieval
- pgvector, Qdrant, Elasticsearch, hybrid and reranked search
- Evaluation
- Custom eval harnesses, LLM-as-judge panels, regression suites
- Infrastructure
- AWS, Google Cloud, Kubernetes, Vercel, Postgres
- Languages
- Python, TypeScript, Go, SQL
We ship to production
A prototype that impresses in a demo and fails under load is not a result. We are judged on what runs.
We measure before we claim
Model quality is an empirical question. We build the evaluation before we build the confidence.
We hand back ownership
The engagement ends with your team able to run, debug and extend the system without us.
05 / Questions
Frequently asked
- What does Hokayantra Technologies do?
- Hokayantra Technologies is an AI engineering consultancy based in Mumbai, India. We design and build production systems on top of large language models, autonomous agents and retrieval infrastructure, and we take responsibility for how those systems behave under real traffic rather than in a demo.
- How is an AI engineering consultancy different from an AI agency?
- An AI engineering consultancy is accountable for the system in production, not the pitch. Hokayantra Technologies works on evaluation, guardrails, cost and latency budgets, observability and rollback, which is the work that decides whether an AI prototype ever becomes a dependable product.
- What services does Hokayantra Technologies offer?
- Hokayantra Technologies works across six practices: applied LLM systems, autonomous agents, retrieval and knowledge infrastructure, evaluation and reliability, data and platform engineering, and AI product engineering. Most engagements draw on several at once, because production AI rarely fails in only one place.
- How do engagements with Hokayantra Technologies work?
- Hokayantra Technologies offers three engagement models. A discovery sprint runs two to four weeks and establishes whether an AI approach is viable and what it costs to run. A build partnership runs three to nine months and delivers a system into production. An embedded team places senior engineers inside your organisation on an ongoing basis.
- Which AI models and technologies does Hokayantra Technologies use?
- Hokayantra Technologies is not tied to a single vendor and selects per problem. That includes Anthropic Claude, OpenAI and Google Gemini alongside open-weight models, orchestration through the Model Context Protocol and LangGraph, retrieval on pgvector, Qdrant and Elasticsearch, and delivery on AWS, Google Cloud, Kubernetes and Postgres.
- Where is Hokayantra Technologies based and who does it work with?
- Hokayantra Technologies is based in Mumbai, India, and works with clients worldwide. Enquiries go to support@hokayantra.in.
Let us talk about what you are building.
Tell us the problem and the constraints. We will tell you honestly whether AI is the right tool for it.