Hackathon-based hiring
Run an invention challenge on the lab floor with a real problem statement, arms, sensors, Jetsons, and GPUs; assess candidates through working prototypes.
Planning estimate · Rs 2-5 L per edition + per-hire feeServices · deployments · research
Build here, or bring the lab to the site.
Armature AI Labs is developing a robotics floor and engineering services for organizations that need working hardware, private AI infrastructure, or credible physical datasets. We are pre-launch and accepting enquiries.
01
Talent and training
The fastest way to find, grow, and test hardware talent is to watch it build. Armature AI Labs runs that room.
Employee training
Private invention-lab cohorts covering edge AI, embedded systems, Jetson vision, local LLMs, and robotics fundamentals, ending in a demonstration.
Planning estimate · Rs 1.5-4 L per cohortStudent research programs
Semester-long, industry-linked edge AI and physical AI projects supervised in the lab with colleges and companies.
Per student · per batchEdge AI invention sprints
Four-week evening programs using Jetsons, cameras, sensors, and DGX Spark, ending in a certified capstone build.
Rs [rate] per seatPublic workshops
One-day hands-on formats for small batches. Member booking options remain visible on the Membership page.
Planning estimate · Rs 5,000-10,000 per seatDemo days and meetups
Use the demo floor, AV, and working equipment as the setting for launches, meetups, and live demonstrations.
Planning estimate · Rs 25,000-75,000 per eveningAll figures are INR-first planning estimates, not quotes. Final scope, cohort size, hardware, and staffing determine each proposal.
02
Build and research services
Hand over a brief or bring researchers to the benches; the same floor that trains builders also does commissioned work.
Prototyping as a service
Brief in, working prototype out: engineering, printers, CNC, electronics, and test equipment.
Planning estimate · Rs 2-15 L per projectCommissioned datasets
Manipulation, vision, and site-specific datasets collected on lab rigs and annotated to a defined specification.
Per projectResearch residencies
Bench, equipment, and collaboration for research professionals and corporate R&D teams.
Monthly residencyEquipment with operator
The arm or camera rigs with a lab engineer operating the test and safety process.
Day rateMember maker desk
Secure project lockers, build-sized consumables, and complete portable toolkits for everyday fabrication work.
Member pickup + rentalHardware sourcing and BOM
Component specification, vendor comparison, imports, compliance checks, and assembly planning so teams can start building.
Fee + approved procurement marginZone sponsorships
Hardware brands can support a bench, a demonstration station, or a workshop series used by the builder community.
Annual plan03
Design, build, and run a local AI data centre
For organizations that want GPUs on their own premises, Armature AI Labs can take a deployment from workload sizing and bill of materials through burn-in and ongoing operation.
Design
Size the GPU, storage, networking, power, and cooling for the workload and budget, from a two-GPU workstation to a larger rack.
Build
Assemble and burn-test the system in the lab; validate PCIe topology, firmware, drivers, thermals, and sustained training or inference.
Run
Install on the customer network with monitoring, recovery procedures, updates, and optional managed capacity planning.
Hardware, engineering, and managed-operation costs are scoped separately in INR after a current bill of materials and site-power review.
04
Why on-prem physical AI
Continuous camera and sensor workloads need predictable latency, a controlled data boundary, and infrastructure that can serve more than one local use case.
01
Continuous video stays local
An on-site GPU processes camera streams in real time without round-the-clock cloud transfer.
02
Footage remains inside
Sensitive video, documents, and model queries stay within the organization's premises and access policies.
03
One stack serves many jobs
The same local compute can support safety analytics, dashboards, document search, assistants, and site-specific models.
04
The lab remains behind it
Armature AI Labs specifies, deploys, tests, and maintains the system as workloads and operational needs change.
Existing cameras + sensors
CCTV and site sensors remain the operational inputs.
Jetson-class edge boxes
Local ingest, filtering, and bounded low-latency inference near the source.
On-prem GPU server
Private model serving, video analytics, storage, and local LLM workloads.
Alerts + local applications
Dashboards, safety events, search, and assistants stay available on the customer network.
Architecture: cameras and sensors to edge boxes to the on-prem GPU server to local alerts, dashboards, and LLM applications. Operational data does not need to leave the site.
05
Who it is for
Hospitals
Patient-area monitoring, fall or restricted-zone alerts, and hygiene workflows under hospital-controlled data policies.
Malls + hotels
Footfall, crowd flow, queue analytics, incident detection, and guest-safety operations across public spaces.
Factories
PPE and safety signals, intrusion alerts, line monitoring, and visual inspection around existing equipment.
Schools + institutes
Entry, perimeter, attendance signals, and after-hours anomaly review under campus control.
Private knowledge teams
Local assistants, document search, and reporting on the same on-prem GPU infrastructure.
Teams learning physical AI
Hands-on workshops using Jetsons, DGX Spark, sensors, cameras, and robotics equipment in the lab.
06
How an engagement runs
01
Assess
Review cameras, workloads, footfall, privacy constraints, network, power, and intended operating outcomes.
02
Pilot
Prove one bounded use case in one zone, with measurable acceptance criteria agreed before deployment.
03
Deploy
Install edge boxes, GPU, storage, networking, models, monitoring, and recovery procedures on site.
04
Operate
Monitor the system, review incidents, update models, and plan capacity through a managed-service period.
05
Expand
Add zones, cameras, models, and local LLM workloads on the same controlled architecture.
Commercial planning separates the one-time assessment and pilot, deployment hardware, and any monthly managed service. Final INR pricing follows a site assessment and current vendor quotes.