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Ontogenesis Technologies

Service

AI services

Strategy, prototyping, engineering and operation of AI systems — from first workshop to the thing running in production.

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Our AI practice covers the full arc: deciding what to build, proving it quickly, engineering it to production standard, integrating it with the systems that matter, and running it afterwards.

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We are model-agnostic and deployment-agnostic by design. Hosted APIs where they are appropriate, open-weight models inside your own boundary where residency, cost or control demand it — decided on your requirements rather than a partner incentive.

The detailed capability breakdown lives in the AI & Agentic AI section; this page describes how we engage.

What you get

  • Evidence early, before large commitments
  • Production systems with measured quality
  • A team that can operate what was built

What's included

AI strategy and discovery
Scored use case portfolios, data readiness, architecture direction and a costed roadmap.
Prototyping
A working prototype on your data in weeks, built to be judged and discarded if it fails.
AI engineering
Production systems: retrieval, agents, evaluation, guardrails, observability and cost control.
ML engineering
Classical machine learning where it is the better answer — training, deployment and drift monitoring.
AI integration
Embedding capability into enterprise platforms and custom applications with fallbacks.
Managed AI operations
Ongoing evaluation, model updates, incident response and spend management.
Where this applies
  • A board-level AI mandate with no agreed starting point
  • Pilots that work in demos and never reach production
  • An AI feature needed inside an existing product
  • A model in production that nobody is monitoring
Technologies
  • OpenAI GPT models
  • Mistral
  • LLaMA
  • Ollama
  • LangChain
  • CrewAI
  • Semantic Kernel
  • Hugging Face
  • Pinecone
  • Weaviate
  • ChromaDB
  • Milvus
  • PyTorch
  • TensorFlow
  • scikit-learn
  • XGBoost
  • Python
  • FastAPI
Engagement models
  • Discovery sprint. Two to three weeks. Scored use cases, data readiness, architecture direction, costed roadmap.
  • Prototype. Fixed scope, fixed duration. One use case, your data, a clear go / no-go at the end.
  • MVP to production. Iterative delivery in two-week increments against agreed outcomes.
  • Embedded team. Our engineers integrated into your delivery organisation.
  • Managed AI. Ongoing operation under an agreed service scope.

Related services

Ready to talk about AI Services?

Tell us about the process or problem, and we'll tell you plainly whether this is the right starting point.

Talk to an AI engineerSee our methodology

Or reach us directly at info@ontogenesistechnologies.com · +91-9999101853