HC Labs · Sovereign enterprise AI
Sovereign AI.Owned. Governed. Deployable.
Protected AI infrastructure for critical enterprise processes — deployed inside the customer perimeter and independent of public AI APIs.
25+25+ years in cybersecurity, fintech and critical infrastructure
Sovereign AI perimeter● ONLINE
Your private cloud
HC / COREAgent network
01Private knowledge
02Open models
03Corporate data
Public AI APIsNo data transfer
Evidence / At a glance
01 / Market problem
Enterprise AI has an ownership problem.
Critical workflows cannot depend on external pricing, changing API policies or uncontrolled data movement. HC Labs turns that constraint into a product thesis.
Sensitive context must stay controlled
Corporate knowledge, prompts and outputs remain within the customer’s security and governance boundary.
Models must remain replaceable
Business logic survives model, provider and infrastructure changes instead of being rebuilt around one API.
Autonomy requires accountable control
Every agent action needs policy, traceability, evaluation and a defined human approval boundary.
02 / Architecture
One protected flow. Three deployment modes.
Data, knowledge, agents and models operate as one governed system. The deployment changes; the ownership principle does not.
LOCAL / ACTIVE MODE
Customer-owned infrastructure
Models, knowledge and operational logs remain on hardware controlled by the organization.
01Local inference02Private RAG03Enterprise identity
03 / Platform
A product architecture, not a collection of disconnected projects.
Five ownable layers turn protected enterprise AI from bespoke integration into a repeatable platform.
HC / GUARD
Identity & policy layer
Access control, encryption, DLP integration and policy enforcement around every human, agent and data source.
Ownable layer · Security and governance remain inside the customer perimeter.HC / KNOWLEDGE
Private knowledge layer
Local RAG, document intelligence and governed access to proprietary corporate knowledge.
Ownable layer · Internal context without public-API exposure.HC / AGENTS
Agent orchestration
Specialized agents coordinate analytical, reporting and operational workflows with explicit approval gates.
Ownable layer · Repeatable automation with humans in control.HC / MODELS
Model-neutral runtime
Llama, Mistral, Qwen and other models can be replaced without rebuilding business workflows.
Ownable layer · No structural dependency on one model or API provider.HC / CONTROL
Audit & observability
Traceable actions, evaluation, monitoring and expert review for production-grade AI operations.
Ownable layer · Evidence for security, compliance and continuous improvement.04 / Evidence
Applied intelligence, shown as evidence.
CASE / 01Confidential engagement
PropTech · Business pivot
~31%growth in financial activityChallenge
Commercial signals were fragmented across existing workflows and difficult to turn into action.
Protected deployment
A process audit and pilot AI agent surfaced overlooked opportunities and enabled a new operating model.
CASE / 02Confidential engagement
RegTech · Auto-compliance
100%human-error risk removedChallenge
Changing fiscal rules created repetitive document rework and avoidable manual risk.
Protected deployment
An autonomous agent tracks requirements and rebuilds reporting documents while retaining expert approval.
CASE / 03Confidential engagement
Enterprise · Europe
40%lower operating costChallenge
Routine operations were costly, but the underlying European data could not leave the controlled environment.
Protected deployment
A protected multi-agent perimeter automated operations while maintaining GDPR-aligned data control.
05 / Team
Security expertise earned where failure is expensive.
SS
Founder & Lead ArchitectStanislav ShevchenkoLinkedIn profile ↗
25+ years across international cybersecurity, exchange infrastructure, banking security and enterprise AI R&D.
11 yearsKaspersky Lab
8 yearsExchange Information Center
6 yearsSberbank ATM security
5+ yearsAI systems R&D
06 / Deployment
A clear path from uncertainty to controlled deployment.
Audit & risk analysis
We map processes, infrastructure, constraints and privacy requirements.
2–3 architecture paths
You compare realistic options by autonomy, budget and time-to-value.
Deploy inside the perimeter
Models, knowledge and agents are integrated without creating new external dependencies.
Pilot & transfer ownership
A focused PoC proves value, then code and operational control move to your team.
07 / Principles
Pragmatic AI, built beyond the hype cycle.
A business-critical system should not stop because a provider changes its price, policy or availability. We design for ownership and resilience from day one.
Complete ownership
You own the code, model weights and local knowledge bases. The system is transferable by design.
Hot-swappable models
Replace Llama, Mistral, Qwen or another model without rebuilding the business logic around it.
Operational autonomy
Run on-premise or in a private cloud, including inside isolated environments without public internet.
CAPITAL / Open dialogue
We are opening the next stage of HC Labs.
We welcome focused conversations with investors, grant programs, accelerators and strategic partners who understand deep-tech infrastructure and long enterprise cycles.
Investment
Productization, team capacity and enterprise go-to-market.
Grants
Research programs in sovereign AI, security and autonomous systems.
Partnerships
Pilots, distribution, infrastructure and strategic market access.
Next-stage objectives
01Productize the reference architecture
02Validate strategic enterprise pilots
03Build grant-backed R&D work packages
04Scale a repeatable enterprise go-to-market
NEXT / Contact
Start with the thesis, the team and a serious conversation.
Tell us whether you represent capital, a grant program or a strategic partner. We will continue with the relevant materials and a focused discussion.
Start a confidential dialogueFounder-led · Confidential · Evidence-first