The layer where your data starts to mean something.
Nirukta Labs is an applied studio for frontier systems — knowledge graphs, reasoning layers, and agentic architecture that turn scattered enterprise data into decisions a machine can act on. Named for the Vedic science of deriving meaning; built for the age of machine understanding.
just data
not beside it
from day one
Four disciplines, one intelligence layer.
We work where frontier tech meets real operational weight — turning raw enterprise data into systems that know what it means, then act on it.
Applied AI & data intelligence
Knowledge graphs, GraphRAG, and reasoning layers that turn scattered enterprise data into decisions — an independent intelligence layer you own, not a black box you rent.
Explore →Agentic systems & orchestration
Multi-agent workflows and an orchestration layer that sits above your existing tools — coordinating ServiceNow, SAP, ERP and the rest — instead of becoming one more silo.
Explore →Domain platforms
Vertical systems where the stakes are highest and the data is hardest — starting with healthcare supply-chain orchestration, from procurement signal to clinical availability.
Explore →Emerging compute & architecture
Edge, probabilistic, and post-binary paradigms. Reference architectures and advisory for the systems that come after today's LLM.
Explore →Built for domains where meaning is mission-critical.
We go deep where the data is hardest and the cost of being wrong is highest.
Healthcare
Supply-chain orchestration and operational intelligence — from procurement signal to clinical availability, where a stockout is a patient-safety event.
Explore →Life sciences
Connecting research, regulatory, and commercial data into one traceable model — so decisions inherit provenance, not guesswork.
Explore →Supply chain
Turning fragmented logistics, supplier, and inventory signals into a graph that anticipates disruption instead of reporting it late.
Explore →The problem isn't more data.
It's that nothing agrees on what it means.
Every system has its own definition of the same thing, so reports conflict and AI hallucinates. We model the entities, relationships, and rules underneath explicitly — the meaning layer both people and machines can reason over. Read the thesis →
Discovery & semantic audit
Map the systems, define the core ontology, and pick one high-value slice worth grounding first.
Graph pilot
Build the graph for that slice, wire up GraphRAG, and prove grounded, traceable answers against real questions.
Production hardening
Pipelines, governance, access, and observability — integrated into your stack and ready for real load.
Scale & operate
Extend the ontology, add agents and use-cases, and hand over or co-run with your team.
Give your data a shared meaning.
Bring one messy, high-stakes question your systems can't answer today. We'll show you what grounding it would take.
Book a working session