BivectorAI is a deep-tech infrastructure company developing deterministic, evidence-bound assessment workflows for AI software assurance and selected industrial and scientific tracks. Outputs include provenance records, tamper-evident hash manifests, and explicit claim boundaries designed for independent technical review.
Không phải SaaS thông thường. BivectorAI xây dựng các quy trình đánh giá kỹ thuật có bằng chứng, nguồn gốc dữ liệu, manifest phát hiện sửa đổi và biên tuyên bố rõ ràng. Kết quả vẫn cần được chuyên gia độc lập kiểm tra theo từng lĩnh vực.
12 domain clusters · 64 internally mapped sub-domains · View full domain map →
Industrial teams need assessment records that are traceable, repeatable, and open to technical challenge. BivectorAI develops a common evidence architecture for selected software, scientific, and industrial workflows. Each output records declared inputs, assessment boundaries, provenance, unresolved questions, and the evidence required for the next decision.
Mọi kết quả được thiết kế có nguồn gốc, có thể kiểm tra và phát hiện sửa đổi thông qua manifest/hash; điều này không thay thế xác thực độc lập. Đây là hạ tầng — không phải một sản phẩm đơn lẻ.
Generate and rank candidates across materials, molecules, quantum workloads, sensor configurations, and infrastructure states — with explicit evidence and claim boundaries on every result.
Every output is packaged into a customer-readable dossier: what was assessed, what passed, what remains unproven, and the recommended next step. Formatted for expert review, not internal use.
VSCode extension and CLI designed for local and air-gapped execution. Network dependencies, data-transfer behavior, and customer-boundary requirements are verified and documented for each pilot.
Subject to a signed agreement, partners may receive scoped platform access, API rights, and licensing terms tied to the applicable filed, confidential, or trade-secret boundary. BPUQ native quantum-hardware research remains a separate long-horizon direction.
BivectorAI maintains an internal technical map spanning 64 application domains across twelve clusters, from atomic-scale material candidates to large-scale infrastructure and Earth-system research. AI Software Assurance is the commercial entry point. Domain mapping does not imply equal maturity, production readiness, regulatory approval, or patent filing coverage. Filing status must be verified part by part.
Geometric inspection of AI-generated code changes. Protected-path policy enforcement, dependency drift detection, reproducible evidence reports. VSCode/CLI with local and air-gapped enterprise deployment. The first commercial product. Available for bounded customer validation.
Structured candidate assessment for quantum materials, superconductors, semiconductors, batteries, and catalysts. Evidence packs with explicit claim boundaries and provenance records — no experimental results are claimed without independent lab validation.
Molecular and biological candidate ranking with identity controls, provenance records, novelty boundaries, and CRO-ready dossiers. 253 preregistered drug-candidate packages prepared for expert handoff. Clinical and experimental validation explicitly outside the dry-lab claim.
Quantum workload assessment, artifact inspection, execution provenance, reproducibility records, and post-quantum cryptography migration evidence packs. Hardware compliance requires independent validation.
Beamtime readiness records, experiment configuration evidence, computational lineage, and HPC milestone packages. Designed for technical review before scarce facility time and budgets are committed.
Sensor-state stability assessment, industrial robot telemetry analysis, counter-UAS sensor fusion, GPS-denied navigation evidence, and action-boundary records. Assurance and decision support — not autonomous safety certification.
Energy grid stability analysis at 5-second resolution, renewable integration evidence, cooling and power-flow topology assessment, datacenter infrastructure state records. Advisory outputs — kept separate from direct operational control.
Software and configuration lineage, causal incident reconstruction, change records and review boundaries for OT, ICS, and SCADA environments. Local and air-gapped deployment options are assessed against the customer's actual infrastructure, dependencies, and data boundary.
Policy-to-evidence mapping, provenance-preserving records, and privacy-aware signatures for regulated technical systems. Regulatory approval, financial assurance, and clinical validity remain the responsibility of qualified independent reviewers.
First-principles research toward BPUQ, a native quantum-hardware architecture derived from BivectorAI physical requirements. Carrier, substrate, fabrication pathway, and measured performance remain unresolved. No fabricated device, measured throughput, or room-temperature hardware result is claimed.
Mission-data provenance, hallucination-firewall assurance, logistics readiness records, and chain-of-custody evidence. Air-gapped deployment with customer-controlled cryptographic ownership. Operational effectiveness requires customer testing and validation.
Research artifact indexing, scientific evidence binding, neuroscience and protein-system analysis, reproducibility records and expert-review packages. Diagnostic or clinical claims are explicitly excluded without independent validation.
The figures below come from founder-controlled repositories, preregistered test contracts, deterministic receipts, and internal audit artifacts. They support technical diligence and pilot design — they are not third-party certifications, production approvals, or independent scientific validation.
BivectorAI is available to discuss scoped validation pilots, strategic investment, IP prosecution support, and domain-specific co-development with explicit inputs, outputs, evidence gates, and non-claims. Founder: Dam Van Vi — damvanvi@gmail.com