Introducing humaineeti: agentic AI, engineered to earn its keep
humaineeti engineers governed, outcome-driven agentic AI and generative AI for the enterprise — built for production and trusted from day one. Here…
humaineeti Editor
humaineeti Editor
humaineeti Editor
Naming an AI company when every trust word is already taken
Trustworthy, responsible, ethical — every good word for AI has been pasted onto products that never earned it. Here is how we…
humaineeti Editor
In-country inference and data sovereignty: what local Claude processing on AWS means for regulated India
Anthropic's move to in-country inference for Claude on Amazon Bedrock puts data residency back at the centre of enterprise AI in India.…
humaineeti Editor
India DPDP Act compliance for AI systems: the 2027 deadline and what it means for your architecture
DPDP Rules notified November 2025, full enforcement by May 2027, penalties up to ₹250 crore. What the timeline means for AI training…
humaineeti Editor
LangGraph vs CrewAI vs AutoGen: multi-agent orchestration frameworks compared (2026 benchmarks)
Benchmark data across 100 runs shows LangGraph 2.2x faster than CrewAI and an 8-9x token spread. Plus why AutoGen entering maintenance mode…
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AI agent evaluation in 2026: trajectory metrics, tool-call correctness and cost per resolved task
Agents scored only on final output pass 20-40% more tests than trajectory evaluation reveals. A practitioner guide to the three evaluation layers,…
humaineeti Editor
Evaluation as a service: when to build your AI eval pipeline and when to buy it
Eval-as-a-service exists because building a credible evaluation capability is a sustained commitment. A build-versus-buy framework that separates the generic infrastructure layers from…
humaineeti Editor
The GenAI readiness assessment: what a useful one actually tells you
Most GenAI readiness assessments produce a maturity score and a slide deck. What separates one that changes your roadmap: five dimensions assessed…
humaineeti Editor
RAG engineering in 2026: why retrieval, not the model, sets your quality ceiling
Industry analysis puts the RAG failure point at retrieval roughly 73% of the time. A practitioner guide to chunking, hybrid search, reranking…
humaineeti Editor
The RBI FREE-AI framework, explained for engineering teams
The RBI's FREE-AI report sets out seven sutras, six pillars and 26 recommendations for AI in Indian finance. What BFSI engineering teams…
humaineeti Editor