Too much ground, too little time
Long routes and repeated checks turn valuable inspection time into walking time, while distant equipment receives only brief attention.
Autonomous industrial inspection
Industrial inspection that comes back with proof.
A machine rarely fails without warning. The warning is often a small change nobody saw in time: a warmer motor, a slow leak, a shifted gauge or an open panel. VyuhaSight is being built to find, record and surface those changes on every round.
Currently: complete software funding demo; physical prototype and customer-site validation are next.
Inspection round active
Next stopMotor M-01Visual + thermal check
ConnectionOffline readyLocal map retained
Product design vision · sensor details simplified
01 Repeatable inspection rounds
02 AI and sensor evidence
03 Works without constant cloud access
04 Human-reviewed findings
The problem hiding in plain sight
The expensive failure often begins as a small, missed change.
Teams cover large facilities, many assets and repeated shifts. Even skilled inspectors cannot be everywhere at once or remember the exact condition of every machine from the last round.
No dependable “before”
A photo, reading or handwritten note without the same viewpoint and asset identity makes gradual deterioration difficult to see.
Warning signs stay disconnected
Heat, visual condition and equipment readings may live in separate records, delaying the moment when a pattern becomes actionable.
The change we are building
We are not replacing the inspector. We are changing what an inspection round can remember.
From
“The round was completed.”
→To“Here is what every asset looked like and measured.”From
Isolated photos and readings
→ToA repeatable history that reveals change over timeFrom
Waiting for a serious alarm
→ToEarlier human attention backed by visual and sensor evidenceThe VyuhaSight inspection platform
One round. A complete, reviewable record.
The robot maps a permitted route, stops at registered equipment and collects the observations required for that inspection. Edge AI helps identify known equipment and configurable abnormal conditions. Results remain available locally and can sync when connectivity returns.
- ✓Maps before it patrolsCommission the site once, validate it, then reuse the approved local map.
- ✓Looks from repeatable viewpointsStop at known inspection points and face the correct equipment.
- ✓Keeps evidence togetherConnect images, thermal views, readings and findings to the same asset.
- ✓Uses AI as an inspection assistantComputer vision supports object detection and anomaly screening while people retain review authority.
- ✓Returns safely when power is lowUse the local map to return to the charging point without depending on Wi-Fi.
Inspection result
Recorded evidence
Inspection pointCP-04 · Water pump
CompleteVisual checkCaptured
TemperatureNormal
Evidence files4 verified
Illustrative interface based on the validated simulation workflow.
Adaptive mobility roadmap
Built to keep the inspection moving when the floor is no longer flat.
Wheel and leg mobility platform · in development
Our planned mobility architecture combines the efficiency of wheels on level ground with independently adjustable legs for controlled traversal of steps, thresholds and uneven surfaces.
Concept mobility sequence
Illustrative engineering concept · final geometry, limits and safety controls subject to prototype validation
Why customers and investors care
01
02
03
Discuss a site or development partnership
One inspection intelligence platform. A larger operating envelope.
Adaptive mobility is intended to take the same evidence workflow beyond smooth, single level floors. This opens routes that would otherwise need a second robot, fixed sensors or a manual handoff.
More route continuity
Plan for thresholds, level changes and short stair sections without breaking the inspection record.
Broader deployment potential
Extend the platform toward older factories, utility areas, depots and infrastructure sites with mixed surfaces.
Reusable commercial platform
Pair new mobility hardware with the same autonomy, Asset Memory and customer review workflow.
Development status
Stair and uneven terrain traversal is a product roadmap capability, not a currently validated deployment claim. Prototype testing will define safe step dimensions, slopes, payload, speed, endurance and operating conditions before customer use.
Concept → Prototype → Controlled trials → Site qualification
Asset Memory
The robot does not just inspect. It remembers what changed.
Every accepted inspection strengthens a permanent history for that equipment. Repeat photographs, thermal observations and readings stay connected to the same asset, so teams can review change instead of searching through disconnected files.
- 01Same equipment, comparable viewThe robot returns to a registered inspection point and checks viewing quality.
- 02Change made visibleAligned repeat photographs highlight areas that deserve a person’s attention.
- 03Evidence stays traceableImages and readings retain their time, source, site and calibration identity.
Asset M-01
Repeat inspection comparisonViewpoint checkComparable
Changed areaReview requested
Illustrative interface: the implemented software aligns compatible repeat images and produces a review heatmap. It does not confirm a defect without human review.
How the robot uses AI
AI that can observe, move and act in a real facility.
The robot combines perception and machine learning with autonomous movement: it sees equipment, travels through the site and gathers useful evidence. AI supports inspection decisions without entering the emergency stop or basic motion safety chain.
Computer vision
Identify configured equipment, people and visible conditions from the robot’s inspection camera while operating locally.
Object detection · visual inspection · equipment recognitionAnomaly screening
Combine visual, thermal and equipment readings to highlight changes that deserve human attention.
Anomaly detection · thermal screening · sensor fusionSite adaptation
Use approved inspection history to evaluate improved models offline, then release signed updates with rollback.
Machine learning · model validation · predictive maintenance dataCurrent boundary: AI perception has passed representative simulation testing. Real-camera accuracy, physical thermal measurements and customer-site performance still require validation.
From patrol to useful action
Eight inspection jobs. One traceable operating loop.
VyuhaSight is designed to do more than show a live feed. It revisits registered equipment, looks for change, keeps the evidence connected to the asset and sends a clear finding for human review.
01 Learn the site→
02 Check the same assets→
03 Compare what changed→
04 Deliver reviewable proof
01Equipment health
Catch the small change before it becomes a stoppage.
Screen motors, pumps, conveyors and utility equipment for visible, thermal, sound or vibration changes using the sensors approved for that site.
Repeat viewTrend historyHuman review
02Read and verify
Turn existing gauges and indicators into usable records.
Capture configured gauges, meters, displays, warning lamps and valve positions without replacing the customer’s equipment.
03Abnormal conditions
Surface leak and heat clues with context.
Record visible liquid or steam clues and relative hotspots. Gas detection is enabled only with a validated site specific sensor.
04Safety watch
Notice what a busy round can miss.
Flag configured PPE concerns, people in restricted areas, open panels, missing signs and blocked routes for review.
05Warehouse condition
Check the facility around the inventory.
Observe racks, pallets, packages, dock assets, aisles and safety equipment while leaving material movement to existing systems.
06Cold chain
Preserve evidence around temperature sensitive areas.
Record local environmental context, door state, frost, visible leaks and refrigeration equipment condition on repeat routes.
07Offline autonomy
Finish the round even when Wi-Fi does not.
Use the saved local map, continue approved missions, retain results on board and return to the charging pad when energy is low.
08Asset Memory
Give every important asset a living inspection history.
Connect each accepted image and reading to the correct asset, route, model and time so teams can compare change across rounds and sites.
Product scope: the software workflow is implemented and validated in simulation. Physical detection performance and business results must be proven with the final sensors at each pilot site.
One system, phased markets
Start where the robot fits. Expand where the customer problem repeats.
The first product serves supervised, non hazardous and accessible routes. Adjacent sectors use the same inspection workflow after site, sensor and safety validation. Harsh or hazardous sites need a separately engineered version.
Launch market01
Manufacturing plants
AI assisted equipment condition rounds for pumps, motors, panels, gauges, valves and utility lines in controlled indoor areas.
- Computer vision checks
- Relative thermal screening
- Gauge and equipment evidence
Launch market02
Large warehouses
Computer vision and sensor inspection beyond inventory movement: utilities, dock assets, panels and restricted areas.
- Facility patrol
- Asset condition records
- Safety observation support
Adjacent pilot03
Cold storage
Routine checks around refrigeration equipment, doors and controlled storage areas, with local evidence when connectivity is weak.
- Temperature context
- Leak and frost observations
- Door and equipment condition
Adjacent pilot04
Data centres and utility rooms
Consistent visual and thermal rounds around cooling, power and support equipment on site approved indoor routes.
- Hotspot screening
- Panel and indicator evidence
- Cooling and leak observations
Adjacent pilot05
Rail and fleet depots
Repeatable patrols for workshop equipment, parked assets, utilities and safety conditions on accessible maintenance routes.
- Workshop asset checks
- Visible defect evidence
- Restricted area observations
Adjacent pilot06
Water facilities
Pump, motor, valve and gauge rounds in controlled, non hazardous and robot accessible areas of water facilities.
- Pump and motor condition
- Gauge and valve evidence
- Visible leak observations
Rugged product roadmap
Ports and shipping · power infrastructure · oil, gas, chemicals and mining
These are valuable expansion markets, but they can require outdoor mobility, weather and corrosion protection, hazardous area certification, specialised gas sensing and stricter safety engineering. We will enter them through a funded customer programme after the indoor platform is proven.
Five outcomes we intend to prove
Business value measured at the site, supported by real evidence.
Pilot targets · not achieved results
Each factory or warehouse starts with a measured manual baseline. These ranges become valid only when that site’s pilot data supports them.
Target15–30%lower
Routine inspection cost
Reduce the cost per completed checkpoint with accepted evidence after routes and operations become stable.
Measure: ₹ per accepted checkpoint and ₹ per completed roundTarget20–35%higher
Inspection team productivity
Let people spend more time reviewing conditions and planning work instead of walking, photographing and compiling routine records.
Measure: accepted checkpoints per inspector hourTarget50–80%faster
Timely condition information
Shorten the delay between observing a configured abnormal condition and producing an evidence package ready for review.
Measure: time from capture to review for abnormal findingsTarget25–50%more
Planned inspection coverage
Complete more scheduled equipment checks with the same inspection team across factory utilities or warehouse facility assets.
Measure: accepted scheduled checks per weekLonger term target5–15%lower
Avoidable equipment downtime
Build the consistent condition history needed to surface deterioration earlier and support predictive maintenance decisions.
Measure: downtime hours linked to monitored failure modes01
Baseline four weeks of the current manual process
02
Pilot compare the same routes, assets and accepted evidence
03
Decision scale only when measured value exceeds ownership cost
These are VyuhaSight pilot hypotheses, not guarantees. For industry context only, NIST observed 15% less downtime among surveyed manufacturers relying more on predictive than preventive maintenance; that observational result is not a VyuhaSight robot performance claim. Read the NIST context ↗
How a deployment works
Site knowledge first. Automation second.
- 01
Survey and map
Agree the operating area, measure clearances and create a local map under supervision.
- 02
Register equipment
Define what the robot should observe, where it should stop and what evidence is required.
- 03
Run the round
Navigate the approved route, capture evidence and continue safely when an individual checkpoint fails.
- 04
Review and improve
People confirm findings. Approved data can improve machine learning models for each site through controlled testing and signed updates.
Engineering progress
We show what passed and what has not.
Our current evidence is a complete local software funding demonstration. These results establish the workflow, not physical product performance.
Demonstrated in simulationPhysical validation next
inspection stops completed in the accepted mission
stored evidence files independently matched
configured factory scenarios passed
computer-vision workflow demonstrated without cloud dependency
1
Software workflowComplete funding demo
2
Funding prototypeNext capital milestone
3
Customer pilotReal-site acceptance
4
Repeat deploymentCommercial proof
Commercial path
Build once, earn through every dependable inspection round.
Our planned model combines deployment revenue with recurring software and service revenue. Pricing will be set only after pilot operating cost and customer value are measured.
Deployment
Site survey, mapping, equipment registration and commissioning for each approved operating area.
Planned setup revenueRobot access
Direct purchase, lease or robot service plan selected for the customer’s operating model.
Commercial model to validateAsset Memory software
Recurring access to inspection history, evidence review, alerts, reporting and fleet oversight.
Planned recurring revenueSupport and expansion
Maintenance, additional routes, inspection recipes and validated AI updates for each site.
Planned service revenueWhat funding unlocks
Turn a complete software demonstration into repeatable proof at a real site.
Capital is intended for measurable product gates. It does not make an unsupported claim of production readiness.
- 01Funding prototypeBuild the four wheel robot and validate sensors, charging, safety and repeatable capture.
- 02Controlled site trialsMeasure navigation reliability, inspection quality and operating cost against manual baselines.
- 03Customer pilotsProve repeat use in indoor factories and large warehouses before broader expansion.
- 04Product ready for deploymentComplete the security, manufacturing, service and applicable compliance work needed to scale.
See the product workflow
Request a guided presentation of the accepted simulation mission, inspection evidence and Asset Memory workflow.
Request a private demo Presented privately with the current evidence and development boundaries.Shape a pilot
Bring a recurring route, known inspection pain and a measurable manual baseline.
Discuss a pilotFund the proof
Help convert the validated software workflow into physical and commercial evidence.
Discuss investmentCurrent evidence is from simulation and local software integration. We have not claimed customer revenue, deployed fleet performance or production certification.
Why VyuhaSight
Autonomy should make inspection more dependable, not less accountable.
Evidence before claims
Every result should point to the observation that produced it.
People remain responsible
AI and machine learning support inspection decisions; they do not silently replace safety judgement.
Built for local reality
Offline operation, maintainable hardware and practical deployment economics for India guide the product.
Work with us
Help turn the evidence into a real deployment.
We welcome pilot sites without hazardous zones, investors and strategic partners who value measurable engineering progress and honest validation.
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