ISR & Multi-INT Provenance / Decision-Data Integrity
Commercial referenceDEF-022
When contacting BivectorAI, quote DEF-022 — ISR & Multi-INT Provenance / Decision-Data Integrity.
Who this is for
ISR fusion analysts and decision-support leads who need to know the freshness and transformation history behind a multi-source intelligence product before it drives a decision.
The problem you already have
A confident-looking product can be built on contradictory evidence
Decision products combine sources with different freshness, uncertainty and transformation histories. Without provenance control, a report can read as coherent while it's stitched together from sources that quietly disagree or are already stale.
Technically compatible with a partner system isn't the same as authorized to send them
A decision-data product can be perfectly interoperable with a mission-partner's system format and still not be authorized for release to that recipient under the applicable dissemination policy. Interoperability and authorization are different questions, and treating them as one is how the wrong product ends up shared.
The review doesn't touch your classified source content
Never requested, and structurally rejected if submitted: classified source content, raw intelligence products, or collection-method details.
Real-World Operational Scenario: The Three Reports That Were Really One
Scenario: An analyst assembles a decision-data product citing three separate reports.
A decision-data product cites three separate reports supporting the same conclusion.
WITHOUT this check: Three citing reports are treated as three independent corroborating sources, boosting confidence in the product.
WITH this check: The provenance graph reveals all three reports trace back to the same original upstream source, translated and re-summarized along the way. Confidence is reported based on one independent root, not three, and the shared lineage is disclosed.
What BivectorAI Provides
Repeated Copies of One Source Are Never Counted as Corroboration
Translations, summaries, and re-ingestions of one upstream source remain one evidentiary root, however many times they're copied or however many systems they pass through.
Freshness Isn't Inherited From Processing Time
A product generated moments ago can still be built on stale observations; observation time, processing time, and product time are tracked as three separate things.
Dissemination Scope Checked Separately From Format Compatibility
A product authorized for one community, classification, or mission question is never silently reused for a recipient or purpose it wasn't cleared for, even when the formats match perfectly.
Contradictions Stay Visible, Never Silently Resolved
Conflicting source reports remain first-class evidence rather than being averaged away — analysts see the disagreement, not a false consensus.
Prove the Gate Before Broader Integration (Zero-Risk Evaluation)
Do not buy the claim. Test the gate.
Feed a synthetic product citing three reports that actually share one upstream source, alongside a product formatted for a partner system it isn't authorized to reach. It succeeds only if it reports one independent root instead of three, and blocks the dissemination it wasn't cleared for.
This initial trial measures common-root detection accuracy and dissemination-boundary enforcement. Commercial scale-up occurs only after measured results prove value in your own lab environment.
What you provide
Redacted source-metadata, freshness timestamps, and transformation-history logs already produced by your ISR fusion pipeline.
What BivectorAI actually hands you
Evidence package
- provenance and freshness classification
- source-contradiction evidence
- transformation-history records
- reviewable decision-data certificates
Integration package
Customer-safe input/output contract, local/private integration boundary, validation fixtures and reviewable evidence artifacts.
Deployment model
Qualified local, private or on-premise integration. No public Defense API and no uncontrolled public execution surface.
Technical disclosure
Customer-visible behavior and evidence are disclosed. Confidential implementation details, protected core methods and internal technical data are not published.
What we will never ask you for
Never requested, and structurally rejected if submitted: classified source content, raw intelligence products, or collection-method details, or your system's core design data. Every submission is checked against this rejection list before any evidence logic runs — a malformed or over-broad submission is blocked and reported back to you, not silently processed.
How it actually runs
Engagement path & current acquisition terms
DEF-022 · Tier C — Strategic Sensing / Infrastructure
Secures a defined diligence and exclusive-negotiation period. Any option credit is agreed in writing as part of the signed commercial terms.
Starting integration engineering, customer-safe adaptation, local/private deployment work, validation and acceptance evidence for the agreed environment.
Scope-dependent consideration for negotiated exclusivity in a defined field, program, platform class, territory and rights scope.
Engineering support, update access, security maintenance, evidence infrastructure and agreed sustainment services.
Applied to attributable net program revenue under the definitive agreement, subject to negotiated exclusions and accounting rules.
Commercial boundary. These are indicative starting terms, not a binding offer. Final price depends on exclusivity scope, field of use, territory, sublicensing, technical-data rights, integration obligations, export-control review, support requirements and definitive agreement.
IP boundary. Exclusive FOU does not automatically transfer ownership of BivectorAI Background IP. Worldwide/all-defense rights, sublicensing, source-level technical-data rights or assignment require separate negotiated consideration.
Scope the DEF-022 diligence and integration boundary
Request DEF-022 Acquisition Discussion →Email fallback: contact@bivectorai.com
Defense technology is integrated through qualified local/private engagement. No public Defense API and no automated Defense checkout are provided.