Maven is now a $1.5B program of record
In March 2026, Deputy Defense Secretary Feinberg issued a directive making Maven Smart System the Pentagon's primary AI platform, consolidating AI investment under a single program of record. The budget trajectory: $103M in FY2025, $240M in FY2026, over $1.5B requested for FY2027. Combined with more than $2B requested for CJADC2, the Pentagon is betting nearly $4B per year on AI-enabled command and control.
That money buys a system built for combatant commands and operations centers, and it has earned the investment. Maven ingests satellite imagery, signals intelligence, and multi-source feeds, then delivers fused intelligence products to analysts and commanders. The design uses what those echelons have: connectivity, centralized compute, and trained staff.
A second layer starts where the link ends
A dismounted operator 40km from the nearest relay, running a surveillance position in contested spectrum, cannot reach any enterprise platform when the SATCOM link drops. That is a property of the link, not a flaw in the platform. The team still needs threat assessment, pattern analysis, and ISR fusion in that window.
The January 2026 DoD AI strategy memo requires AI that operates 'on-board, in real time, and often without any sort of connectivity or centralized compute resources.' That requirement describes a different layer from the one Maven serves. Ukraine and the South China Sea have already disproven the assumption that connectivity will be available when it counts.
Enterprise reach depends on the edge
Enterprise funding buys compute, analyst seats, and fusion at the operations center. Local inference on a laptop in a hide site or detection on a phone at a checkpoint is a separate, much smaller line. Funding it makes the enterprise investment worth more, because the data the enterprise fuses starts with those teams.
The Foreign Affairs Forum covered America's algorithmic arsenal spending. Most of the money goes to echelons that already have bandwidth, power, and compute. The lower echelons, where decisions happen fastest and links are worst, need a complementary architecture.
What the team runs when reach-back is gone
When the link drops, the operator needs local object detection on the device. Local threat analysis correlating cameras with RF. Local transcription of intercepted comms. Local mission state so the team knows where everyone is. All generating evidence with chain-of-custody metadata, not disappearing when the connection times out.
EdgeLance runs that stack on the kit a unit already fields. A rugged laptop or server is the command node with full inference. Issued handhelds are field nodes with detection and mesh relay. It does not compete with Maven or replace what Maven does well. It keeps the team working while disconnected and returns attributed data over open standards when the link comes back. How the two layers fit together.