Kenzed Tech Lab designs, builds, and deploys custom AI agents, machine-learning systems, voice AI, and enterprise software — production-grade, secure, and running on infrastructure we own and operate 24×7.
Software is entering its agentic era. Kenzed Tech Lab helps organizations make that leap. We combine deep AI research capability with disciplined software engineering to deliver intelligent products that create measurable value: autonomous agents that handle real workflows, machine-learning models that turn data into decisions, and beautifully engineered applications that people love to use.
Stage 01 / 06 — Scope
A short, paid discovery that turns an ambition into a scoped system with a measurable definition of done.
Stage 01 / 06 — Scope
A short, paid discovery that turns an ambition into a scoped system with a measurable definition of done.
Stage 02 / 06 — Architect
Architecture, data flow and hosting are settled together, because running on our own GPUs changes the design and not just the invoice.
Stage 03 / 06 — Build
Agents, models and interfaces are built in parallel by one team and demonstrated on real data at the end of every sprint.
Stage 04 / 06 — Evaluate
An evaluation harness is a deliverable in its own right — a regression should fail a build, not a customer.
Stage 05 / 06 — Deploy
The same containerised build runs in your cloud account or on our Durgapur GPU cluster, with a rollback measured in seconds.
Stage 06 / 06 — Improve
Traces, drift alerts and a standing backlog keep the system earning its place long after the launch announcement.
Almost every engagement resolves into one of three architectures, or a composition of them. Knowing which one you are in from the very start is what keeps a build predictable: it decides the data contracts, the evaluation strategy and the hardware long before it decides the code.
An orchestrator decomposes the task and delegates to specialised agents that retrieve, reason and act through your real APIs — with shared memory, bounded permissions and human approval on anything consequential.
Ingestion, enrichment, inference and serving as one versioned pipeline, with a feature and vector store every model reads from. Retraining is scheduled, and drift is a monitored signal rather than a surprise.
A router sends each query down the cheapest path that can answer it — vector search, a knowledge graph, or a frontier model — and one graph definition holds the fallbacks, retries and cost ceilings.
Research, engineering, design, QA, and hardware in one team — no handoffs to third parties.
On-premise GPU compute, 24×7 power, and secure facilities for private and sovereign AI.
We don’t stop at prototypes; we ship, monitor, and optimize live systems.
Clear scopes, agile delivery, and dedicated teams that feel like your own.
Clinical documentation agents draft notes from dictation and route every draft to a clinician for approval before anything reaches the patient record.
Course-aware tutoring agents grounded in the institution's own material, with a teaching dashboard that shows which sources each answer was built from.
Demand and routing forecasts served behind an internal API, retrained on a schedule and monitored for the drift that quietly degrades a model.
Document intelligence extracts and cross-checks fields from scanned forms, escalating anything under a confidence threshold to a human reviewer.
Computer-vision inspection running at the line on hardware we specified, flagging defects without a single frame leaving the site.
Engagement patterns described by sector rather than by name. We publish client specifics only where we have written permission to do so.