Systems already running.
Four AI solutions we deliver into enterprise operations, and five platforms we own and operate — several of them inside air-gapped defence estates.
AI solutions
These start from a problem in your operation rather than from a product.
OCR plus agents that find the pages that matter, read unclean scans in 20+ languages, and relate values across a bundle.
Three pages of a 180-page bundle actually matter.
ExploreReal-time voice that answers immediately, handles interruption and accents, and finishes the task on the call.
Calls queue, and the bot cannot actually do anything.
ExplorePlugSafe turns existing CCTV into a real-time sentry — 16 detection types, alerts in seconds, fully on-premise.
The cameras record everything and catch almost nothing.
ExplorePlatforms we own
Engineered in-house, owned end to end, and operated by the team that built them — including inside estates we cannot name.
VR mission planning at terrain scale, built from your own GIS. In service with the Indian Armed Forces.
Defence
ExploreGeospatial intelligence on satellite intercepts — trajectories, group detection, forward projection.
Defence
ExploreAugmented Maritime Awareness — head-up AR for the bridge. Operational with the Indian Navy.
Naval
ExploreTranslation and transcription across Indic languages and English, entirely inside your perimeter.
Sovereign
ExploreConstruction project management across the UK, UAE and India — one record for every party.
Enterprise
ExploreIntfuzon and NOSTRA — multi-channel SIGINT fusion and air-gapped big-data analytics — are covered under Defence.
Start from the symptom
Which one is yours?
Most of these engagements begin as one thing and turn out to be another. Pick the situation that sounds like yours.
Three pages of a 180-page bundle matter.
The material arrives as scans, phone photographs and handwriting, in more than one language, and somebody has to find the pages that count and key the values off them. Accuracy matters more than speed, which is why it has resisted automation so far.
- Bundles far larger than the relevant pages
- Scans, photographs and handwriting mixed
- More than one language in a single set
- Values that must agree across pages
- Manual keying is the bottleneck
- An error has consequences, so nobody rushes
The IVR deflects; it does not resolve.
Callers wait, then reach something that can read a menu but cannot actually do the thing they called about. The existing bot handles the greeting and hands everything else to a person, so the deflection rate looks good and the queue does not move.
- Hold times that customers complain about
- A bot that answers but cannot complete tasks
- The same few call types dominate volume
- Agents look up the same systems every call
- Accents and code-switching break recognition
- Out-of-hours means no service at all
Footage is reviewed after the incident.
There is coverage, and it is used to establish what happened rather than to prevent it. Nobody can watch every feed continuously, so detection depends on someone happening to look at the right screen at the right moment.
- Existing CCTV estate already installed
- Footage used forensically, not preventively
- No realistic way to watch every feed
- Specific hazards you need caught in seconds
- Alerts must be defensible, not guesswork
- Nothing may be sent to a vendor cloud
Five of these already exist and run.
HoloMap, Jatayu, Amara, Bhaasha and Aedrix are products we own and operate rather than projects we would start. If your requirement is one of mission planning, satellite movement analytics, the naval surface picture, sovereign Indic language work or construction project control, the conversation starts much further along.
- Fielded systems, not proposals
- In service with the Indian Armed Forces and Navy
- Deployable inside your perimeter
- Indian OEM, GeM-listed
- Configured to your estate, not rebuilt
- Timeline measured against deployment, not development
Three pages of a 180-page bundle matter.
The material arrives as scans, phone photographs and handwriting, in more than one language, and somebody has to find the pages that count and key the values off them. Accuracy matters more than speed, which is why it has resisted automation so far.
- Bundles far larger than the relevant pages
- Scans, photographs and handwriting mixed
- More than one language in a single set
- Values that must agree across pages
- Manual keying is the bottleneck
- An error has consequences, so nobody rushes
Not sure which one fits?
Describe the problem rather than picking a product. Most of these engagements start as one thing and turn out to be another.