BisonTech fuses every sensor into one picture, watches it around the clock, and holds a decision ready — so commanders act on understanding, not on raw feed.
This is a live, deterministic simulation of the BisonTech pipeline — real gated association, real Kalman state estimation, real anomaly scoring, real human-in-the-loop authorization, running at frame rate.
BisonTech runs a continuous intelligence loop — ingesting every sensor feed, correlating it into a maintained track picture, scoring it against learned baselines, and holding a decision ready. No shift change. No watch rotation. No gap where nothing is watching.
Air, maritime, ground, space and SIGINT feeds polled on their own cadence — never on a human's.
Every observation is gated, associated and filtered into a maintained track picture.
Baselines are learned continuously; deviation from them is scored, not eyeballed.
When a pattern crosses threshold, courses of action are already drafted and waiting.
State is hashed into an append-only ledger on a fixed cadence, around the clock.
Six sensor families arrive as raw, noisy, unlabelled observations. BisonTech gates them, associates them, and maintains a single track picture where every contact carries its own uncertainty — and its own sources.
Observations are matched to tracks only inside a Mahalanobis gate, so a distant blip can never corrupt a maintained track.
Each track carries a full state covariance. Position, velocity and uncertainty are propagated and corrected every sweep.
Confidence is earned, not asserted — independent corroborating sources raise it, and it decays the moment they stop.
Normal behaviour is learned per picture. Deviation is scored against that baseline instead of a fixed threshold.
The pattern engine watches the fused picture against learned baselines. When something deviates, the decision layer drafts courses of action with their confidence, risk and time-to-effect — and then stops, and waits. Nothing moves until a commander authorizes it.
When there isn't enough history to judge, the engine says so — insufficient_history is a first-class result, not a silent zero. Absence of evidence is reported as absence of evidence.
Every recommendation carries the reasoning that produced it, the counter-argument against it, and the operator who signed it. Rejected options are kept too — the ones you didn't take matter.
Intelligence is only useful if you can trust it and account for it. The loop is continuous, and every stage of it is auditable — including the parts that stayed silent.
Six sensor families collapsed into one maintained picture, every contact carrying its own covariance and its own sources.
31 detectors scoring the picture against learned baselines — and saying so plainly when the baseline isn't there yet.
Courses of action drafted with confidence, risk and time-to-effect — then held for human authorization. Never autonomous.
Every state change hashed into an append-only ledger. The reasoning, the rejection, the signer — all reconstructable.
The architecture enforces human supremacy over the decision layer. AI drafts, correlates and explains. It does not authorize. That boundary is structural, not a policy promise.
No autonomous kinetic action. Level 3 and 4 orders require simultaneous cryptographic sign-off from two roles.
Unstructured intelligence is isolated from model prompts, closing the prompt-injection and data-poisoning path.
Actions are partitioned from read-only intelligence through to lethal — and gated differently at each tier.
An append-only hash chain over decisions, evidence and operator sign-offs. Tamper-evident, not tamper-claimed.
Schedule a classified technical briefing with our engineering team to review fusion accuracy, decision thresholds, authorization flows, or configure a sovereign pilot in your air-gapped environment.