Sovereign AI Infrastructure · Vancouver, BC · Canada
Local-first deployment. Audit-ready automation. Human-controlled agents. For organizations that cannot treat data, autonomy, or compliance casually.
Public Sector
Controlled AI for regulated environments.
Local inference. Audit trails. Privacy-first architecture designed for procurement review.
Enterprise Security
Autonomous workflows. Human accountability.
Approval gates, rollback paths, and model-call logging built in from the start.
Deep-Tech Lab
Operator-built. Evidence-first.
Twenty years of operational thinking, now applied to AI risk and agentic control.
Every system ShadowCore builds begins with the same question: what does a human need to see before approving this action?
Private LLM deployment and inference pipelines on hardware you control. No data leaves your boundary. No cloud dependency in sensitive workflows.
Agents with human-in-the-loop approval, structured audit logs, rollback paths, and step-level traceability. Autonomy is earned incrementally.
Structured evidence collection, control mapping, and audit-ready reporting. Designed with SOC 2 and ISO 27001 readiness in mind.
Grafana/Prometheus-style dashboards, structured log pipelines, and network observability using open-source tooling.
Andrey Zaykovskiy is the founder and principal architect of ShadowCore AI, based in Vancouver, British Columbia.
Before AI systems, Andrey built and scaled a construction and exterior remodeling business over more than two decades — managing complex projects, contractor relationships, operations risk, and real-world accountability. That operational background informs everything at ShadowCore: a preference for systems that work over systems that look good in demos, and a deep respect for the cost of failure in production environments.
The transition into AI systems was not a pivot away from operations — it was a continuation of the same problem. Organizations are being asked to trust autonomous systems with consequential decisions before the controls, evidence workflows, and accountability structures are in place. ShadowCore exists to close that gap.
Andrey's current focus is agentic control layers, local AI infrastructure, secure automation design, and AI governance readiness for organizations operating in regulated or risk-sensitive environments. He approaches each system as an integrator and architect — with operator-led judgment about what actually needs to survive contact with the real world.
20+
Years in operations
Vancouver
BC, Canada
Local-first
Infrastructure stance
Founder-led
No VC pressure, yet
Every engagement is client-controlled, defensively scoped, and documented for auditability. Work can be structured under mutual NDA.
ShadowCore supports evidence workflows and readiness preparation. We do not provide legal certification or formal audit guarantees.
All work is defensive and authorized by the client. No offensive security services are provided.
ShadowCore operates at the intersection of applied AI systems and longer-horizon questions about identity, memory, autonomy, and human context. Not all research is public. Not all research is productized. What is published is published carefully, with attention to ethical implications, privacy boundaries, and responsible use.
Core IP and unpublished technical thesis remain private and are not disclosed without a mutual NDA in place.
How personal context, behavioral history, and identity signals can be preserved, controlled, and transmitted — with explicit consent — across time. Long-term research into digital legacy systems for individuals, families, and future descendants. Privacy is a core constraint, not an add-on.
Multimodal AI systems that incorporate human context — preferences, history, communication patterns — to produce more relevant, private, and individually appropriate outputs. Privacy-preserving personalization without mass-surveillance architecture. Consent and data minimization by design.
Applied research into the conditions under which AI agents can be trusted with increasing autonomy. Focus on control structures, intervention points, accountability chains, and evidence frameworks for regulated deployment. Autonomy is a dial; this research is about the mechanism that turns it.
Translating responsible AI frameworks — NIST AI RMF, ISO/IEC 42001, and emerging regulatory guidance — into operational controls, audit-ready documentation, and governance structures that work in real organizations with real resource constraints.
Research Ethics Statement
All research into human-context AI, digital identity, and behavioral signals is conducted with consent, privacy, and human oversight as non-negotiable design constraints. ShadowCore does not build covert profiling systems, surveillance products, or psychological manipulation tools. Ethical boundaries are design requirements, not advisory guidelines.
Public-sector and regulated-enterprise deployments demand more than general AI capability. They require verifiable data boundaries, documented human oversight, audit-ready evidence trails, and systems that a procurement team can actually evaluate against known criteria.
ShadowCore is preparing its systems, documentation, and operating practices for conversations with regulated enterprise and public-sector stakeholders. Engagements in these contexts can include structured architecture reviews, privacy impact assessments, and risk register documentation.
“Before increasing autonomy, organizations need control — and before deploying control, they need visibility.”
— ShadowCore Operating Principle
Local deployment ensures sensitive data stays within the client's infrastructure. No external model calls in sensitive workflows unless explicitly authorized and logged.
Architecture notes, data flow documentation, privacy impact assessments, and risk registers formatted for structured procurement review.
Autonomous actions require human sign-off. Approval queues, review workflows, and override paths are part of the system design, not optional add-ons.
Known limitations, failure modes, and system boundaries documented clearly. No overselling of AI capability. No hidden dependencies.
Systems designed for local or hybrid deployment where organizations retain full control over model selection, data routing, and inference environment.
Human oversight, explainability where possible, auditability by default, and governance controls aligned with NIST AI RMF and Canadian federal AI guidance.
Canadian context: ShadowCore is based in Vancouver, BC and is building toward alignment with Canadian federal AI, privacy, and cybersecurity guidance — including direction from Canada's Directive on Automated Decision-Making, the Pan-Canadian AI Strategy, and the Canadian Centre for Cyber Security. This represents preparation and design intent, not current certification or government approval.
ShadowCore applies security-by-design principles across its systems and client engagements. Access controls, audit trails, and evidence workflows are built in from initial architecture — not retrofitted before a compliance review.
Work with regulated clients is structured to support their SOC 2 and ISO 27001 readiness journeys, including evidence collection, control documentation, and gap analysis. ShadowCore does not itself hold current certifications under these frameworks; it helps clients build toward them.
Security Controls Applied
Framework Alignment
Disclaimer: Framework alignment references indicate design intent and readiness support only — not formal certification, audit opinion, or legal compliance guarantee. Organizations in regulated environments should engage qualified auditors and legal counsel for independent verification.
Mission control for AI agents in regulated environments. Visibility, approval, evidence — before any agent acts.
The ShadowCore Sovereign Control Plane is a mission-control layer for AI agents and secure automation — purpose-built for organizations deploying autonomous systems in regulated or risk-sensitive environments.
Before any agent takes action, the Control Plane provides visibility: what the agent intends to do, what data it will access, what systems it will touch, and what a human approver needs to know. Autonomy is a dial, not a switch — and the Control Plane is how organizations set that dial responsibly.
Approval Queue
File classify: /contracts/Q4-vendor/
Email draft → vendor@partner.io
DB query: SELECT * FROM hr_records
Agent Activity Log
Evidence Vault
EVD-4421
Agent run
2025-01-09 09:14
SEALEDEVD-4420
Approval log
2025-01-09 08:52
SEALEDEVD-4419
Model call
2025-01-09 08:41
SEALEDEVD-4418
Access event
2025-01-09 07:30
SEALEDThe ShadowCore Compliance Agent is a local-first alternative to cloud-hosted compliance platforms — designed for regulated organizations that cannot route sensitive system evidence through third-party SaaS infrastructure. It collects evidence, maps controls, monitors configuration drift, and generates audit-ready reports entirely within your infrastructure boundary.
Local Evidence Collection
Pull evidence from systems within your boundary. No data sent to external services.
Control Mapping
Map technical observations to SOC 2, ISO 27001, or custom control frameworks.
Configuration Drift Monitoring
Track when system configurations diverge from defined security baselines.
Audit-Ready Reporting
Generate structured evidence bundles formatted for auditor consumption.
User & Access Activity Review
Periodic access reviews and activity summaries with human review checkpoints.
Security Posture Summaries
Plain-language summaries of security state for non-technical stakeholders.
Disclaimer: ShadowCore provides technical support and evidence workflows. We do not provide legal certification, formal audit opinions, or guarantees of regulatory compliance. Organizations should engage qualified auditors and legal counsel for formal compliance reviews appropriate to their regulatory environment.
Regulated organizations — government agencies, healthcare systems, financial institutions, critical infrastructure operators — are under growing pressure to deploy AI. They are simultaneously under growing pressure to demonstrate control, explainability, and accountability over those systems.
The tooling gap is real. Cloud-hosted AI governance platforms require routing sensitive evidence through third parties. General AI agents lack the approval structures regulated environments require. Existing compliance tools were not designed for AI workflows.
ShadowCore is building from first principles: local deployment, human-in-the-loop control, audit-ready evidence, and modular architecture that works in environments where data sovereignty is not optional.
Founder-market fit: Andrey has operated complex, risk-sensitive businesses for over two decades. He understands what accountability, documentation, and failure-mode management look like in practice — not just in frameworks.
Development Roadmap
Phase 1
Active
Consulting & Services Revenue
Client engagements in local AI deployment, secure automation, and compliance evidence workflows. Revenue funds operations and validates market need.
Phase 2
Design
Local Compliance Agent MVP
A privacy-preserving, local-first compliance evidence tool. Positioned as an alternative to cloud-hosted compliance platforms for regulated environments.
Phase 3
R&D
Sovereign Control Plane
The full mission-control layer for AI agents in regulated environments: human approval, audit trails, model routing, and evidence vault.
Phase 4
Future
Public-Sector Pilots
Controlled pilot deployments in regulated environments with structured documentation, privacy assessments, and measurable outcomes.
Phase 5
Future
Platform
Modular platform for sovereign AI governance — control plane, compliance agent, observability stack, and evidence vault — available as licensed or managed infrastructure.
Strategic Investor Profile
What We Can Demonstrate
Early stage. Not all roles funded. Serious people only. Confidentiality is mutual from the first conversation.
Andrey currently covers founder, architecture, strategy, product direction, early systems design, and operations. That is not sustainable at scale. ShadowCore is looking for two to three serious people who want to build something that matters in a space that genuinely needs it.
You do not need to disclose proprietary information, client details, or existing IP before trust is established. Initial conversations are exploratory and confidential. Contractors and advisors with relevant experience in regulated AI, cybersecurity, compliance automation, or public-sector technology are also welcome to make contact.
Strategy, architecture, product direction, operations, and early systems design. Andrey Zaykovskiy.
Own the technical spine: local AI infrastructure, control plane architecture, observability stack, and security posture. You know how to build systems that hold up under audit.
Bridge technical depth and market traction. Shape what gets built, for whom, and when. Comfort with regulated markets, B2B sales cycles, and honest product criticism required.
Future Roles (Pipeline)
ShadowCore publishes research notes and technical memos when the thinking, sources, and limitations are clear enough to be useful. Draft status is shown honestly.
A concept white paper on governed agentic execution, sovereign deployment, and evidence-first control. Authored by Andrey Zaykovskiy.
Read PDFIn development
Digital Legacy: Architecture for Human Context Systems
Digital identity / privacy-preserving personalization
Local AI Infrastructure for Regulated Organizations
Sovereign AI deployment patterns
Compliance Evidence Workflows for AI Systems
AI governance / SOC 2 readiness
The Approval Gate: Human Oversight in Autonomous Pipelines
AI safety / human-in-the-loop design
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