AI-ready target data, validated at source.
Takes a sensor operator from ‘I have seen something’ to ‘I can contribute an AI-ready report with high confidence’.
Every sensor on the battlefield produces data. The question is whether the first report accelerates decision-making or creates work for headquarters.
AiSource attacks the failure at its origin.
Point-of-origin and point-of-impact errors weaken counter-fire, so AiSource checks bearing and distance against the operator’s own position, sanity-checks the grid on the map and tests the report against equipment parametrics, catching impossible detections before they reach the gun line.
Operators still report quickly. The system helps them report correctly.
From raw observation to structured, validated data.
1.Capture
Structured workflows for sighting, BDA, HLR, GMTI and counter-UAS reporting. Guided equipment recognition from authoritative naming. Validation built into the form.
1.Capture
Structured workflows for sighting, BDA, HLR, GMTI and counter-UAS reporting. Guided equipment recognition from authoritative naming. Validation built into the form.
2.Assure
Grid sanity-checking against bearing and range. Equipment parametrics testing. Schema and completeness checks. Configurable rules engine.
2.Assure
Grid sanity-checking against bearing and range. Equipment parametrics testing. Schema and completeness checks. Configurable rules engine.
3.Integrate
Multi-standard output: chat and XMPP today, APP-11(E) as the ecosystem matures. One capture, many standards.
3.Integrate
Multi-standard output: chat and XMPP today, APP-11(E) as the ecosystem matures. One capture, many standards.
Published in the standard each programme requires.
One capture, many standards. AiSource generates and validates at source, then publishes in the format each programme consumes, so the same report reaches the DTW ecosystem, an ASGARD ontology and a SitaWare picture without manual reformatting.
| Programme | Standard |
|---|---|
| DTW | SAPIENT and APP-11. |
| ADDI | APP-11(E). Testing and reference environment. |
| ASGARD | Palantir Ontology. |
| Land ISTAR | Zodiac SDL. |
| XMPP / Chat | MOD Schema. |
| BCIP modernisation | APP-6D. |
| TLAN | MIL-STD-2525. |
| Programme | DTW | ADDI | ASGARD | Land ISTAR | XMPP / Chat | BCIP modernisation | TLAN |
|---|---|---|---|---|---|---|---|
| Standard | SAPIENT and APP-11. | APP-11(E). Testing and reference environment. | Palantir Ontology. | Zodiac SDL. | MOD Schema. | APP-6D. | MIL-STD-2525. |
Measured on exercise, not asserted.
WARFIGHTER EXERCISE
4+
chat rooms
2.7K+
messages
270+
targets surfaced from unstructured chat
Live integration
with the in-service battle management application
‘These platforms auto-populate data from [tactical chat] into [the battle management application], removing the need for the end user to manually populate information on to the CIP layer’.
Intelligence Officer (OF-3), corps-level exercise, 2026.