THE AGENTIC OPERATING SYSTEM

The operating system for sovereign agentic AI.

We architect, build, deploy, and operate agentic AI — on your infrastructure, under your control.

Generating code was never the hard part. The last mile — deployment, integration, governance, and Day-2 operations — is where enterprise AI stalls. We’re the software factory that covers all of it.

SOVEREIGN AI·Reference Architecture for Agentic AI Runtime

AS SEEN ON

  • NYSE WiredWired · Sovereign AI
  • theCUBEEnterprise AI Analyst
  • Research Collective
THE LAST MILE

Generating code was never the hard part.

Enterprises now have agents that write code. But code doesn’t deploy itself. Agents run loose across the org with no harness, no shared context, and no path to production — and the distance between a generated change and a governed, deployed, operated system is exactly where enterprise AI stalls.

DEPLOYMENT

Getting a generated change safely into production — not a pull request that sits.

INTEGRATION

Wiring agents into your ITSM, SDLC, data, and approval workflows — the systems your teams already run on.

DAY-2 OPERATIONS

Observability, evals, and human-in-the-loop once agents are live and the demo is over.

That’s the gap we close — the last mile, covered.

BEFORE / AFTER

From agents running loose to a governed delivery system.

GLOBAL NETWORK TELEVISION NETWORK · DEVELOPER EXPERIENCE

BEFORE AGENTCY

  • Agents scattered across the org — spun up team by team, with no shared harness.
  • No common context: every agent re-discovered the same systems, traces, and tribal knowledge from scratch.
  • Ungoverned actions, no audit trail, and no human checkpoint before changes landed.
  • Content and code QA done by hand, gating every release on manual review.
  • Shadow tooling and no reliable path from a generated change to production.

AFTER AGENTCY

  • A unified context layer reconciling traces, observability, knowledge, and IT/data into one source of truth.
  • Agents operating on top of it across code generation, CI/CD, and SRE.
  • Engineers describe intent in natural language; the system generates, tests, and proposes.
  • Humans approve — every change governed, audited, and reversible.
  • Deployed and operated inside the client’s own perimeter, end to end.
THE SOFTWARE FACTORY

Architecture, code, deployment, and Day-2 — one factory.

One operating model that carries an idea from blueprint to a system running in production — and keeps it running. This is how we deliver the Agentic OS.

01

Architecture

Reference architectures — the SAISS stack, governance models, and analyst-grade specifications your engineering teams build against.

02

Code

Sovereign agentic systems built to the architecture: open-source-first, and substitutable across vendor, model, and framework by design.

03

Deployment

The last mile — into your infrastructure and your ITSM, SDLC, and approval workflows, with governed, auditable rollout.

04

Day-2 Operations

Observability, evals, and human-in-the-loop SRE that keep agents correct, governed, and accountable in production.

THESIS

What we believe about enterprise AI.

DATA SOVEREIGNTY

Your data stays in your perimeter. Always.

Agents reason over your data inside your network, your cloud, your air-gapped enclave. No round-trip to a vendor; no shadow copies in someone else’s logs.

INFRASTRUCTURE INDEPENDENCE

Your runtime, your call.

OpenShift, EKS, EC2, on-prem GPU — we don’t dictate where it runs. Our reference architectures are designed to survive any of them.

LOCK-IN LIBERATION

Vendor, model, and framework risk — engineered out.

We architect your way out of the dependencies that compound: vendor APIs you can’t replace, model providers that change terms, frameworks that churn. Open-source first, swap-friendly by design.

UNDER THE HOOD

“Context beats cleverness.”

Powered by knowledge graphs, multi-agent orchestration, and real-time operational state — all running on open source.

SELECTED WORK

Example projects from enterprises.

Client names withheld. We architect, build, and operate each system below — sovereign, inside the client’s own perimeter.

Global European Car ManufacturerAUTOMOTIVE

One sovereign runtime to replace every fragmented AI tool.

Dozens of systems, no shared context. The blueprint collapses that surface into one — without surrendering control or data residency.

Developers, business users, and executives reach the same secure system through role-specific interfaces.

ROLE
Architecture & design
SCOPE
Enterprise-wide agentic architecture
RUNTIME
Sovereign cloud / on-prem
DATA
Real-time BI + operational
Global RetailerRETAIL · CONTENT QA

A multi-agent pipeline that turns manual content QA into an exception queue.

Training content is decomposed into individual factual claims, each verified against the authoritative source corpus by specialised agents.

Reviewers see only the claims that fail. Self-hosted, end to end, in the client’s environment.

ROLE
Architecture & design
SCOPE
Multi-agent content QA pipeline
GROUNDING
RAG over authoritative sources
DEPLOYMENT
Self-hosted
Global Network Television NetworkMEDIA · DEVELOPER EXPERIENCE

Natural language in. Tested, governed, human-approved API deployments out.

A unified context layer reconciles traces, observability, knowledge, and IT/data. Agents run on top of it across code gen, CI/CD, and SRE.

Engineers describe what they want. The system generates, tests, proposes. Humans approve — inside the client’s perimeter.

ROLE
Architecture & design
SCOPE
End-to-end agentic architecture
RUNTIME
Sovereign cloud / on-prem
PIPELINES
Code gen · CI/CD · SRE
SAISS · SOVEREIGN AI SOFTWARE STACK

The reference architecture for sovereign agentic AI.

Seven layers — the architecture of the Agentic OS. Every component substitutable, every layer inspectable. Built for enterprises that must run on their own infrastructure, and the vendors that serve them.

L7

Governance & Policy

RBAC, audit logging, human-in-the-loop, policy engines, compliance attestation.

L6

Agent Orchestration

Multi-agent runtimes, planners, tool execution, state machines, eval harnesses.

L5

Models

Open-weight LLMs, fine-tuning pipelines, model gateways — vendor-substitutable by design.

L4

Knowledge & Memory

Vector indices, knowledge graphs, retrieval pipelines, long-term agent memory.

L3

Data & Integration

Real-time BI, ETL, change data capture, operational data fabric, ITSM connectors.

L2

Runtime

Containers, schedulers, service mesh, observability — the operational substrate.

L1

Sovereign Infrastructure

On-prem GPU, sovereign cloud, air-gapped enclaves — the physical perimeter your data never leaves.

Open source

SAISS is being authored as a living reference architecture. Specifications, layered diagrams, and architecture decision records will be published as the work matures.

RESEARCH COLLECTIVE · MEDIA, ANALYST & DELIVERY PARTNERS

Part of the research collective.

Agentcy Labs contributes analysis as part of the SiliconAngle, theCUBE, and NYSE Wired research collective — on sovereign agentic AI, infrastructure independence, and enterprise governance.

Featured interview — publishing soon.

NYSE Wired

Featured commentary on enterprise sovereign AI and the architecture decisions facing public-market CIOs.

theCUBE

Recurring analyst presence on agentic AI architecture, infrastructure independence, and enterprise governance.

Deloitte

Joint delivery across agentic architecture, Day-2 ops, and enterprise change management — Deloitte teams implement; we architect.

Supabase

Supabase

Reference vendor in the SAISS data and integration layer.

Open source first

No proprietary runtime. No hidden dependency. Every layer of every architecture we design is inspectable, replaceable, and yours to operate.

GET IN TOUCH

If we’re the right fit, you’ll know in one meeting.

Scoping within two weeks. Written reference architecture and roadmap before any commitment.

THE PARTNERS

Amit Eyal Govrin

Amit Eyal Govrin

Co-founder·LinkedIn ↗

Former CEO of Kubiya (Gartner Cool Vendor; backed by founders of HashiCorp and Slack) — first agentic platform to land LLM-driven automation inside Fortune 500 production. Previously led AWS's global DevOps and DevSecOps partnerships. NYSE Floor Talk and theCUBE regular on enterprise agentic AI.

  • Ex-AWS DevOps Lead
  • NYSE · theCUBE
  • Two-time Founder
Shaked Askayo

Shaked Askayo

Co-founder·LinkedIn ↗

Architecting agentic AI in production since 2022 — pre-ChatGPT. Co-founder and former CTO of Kubiya (Gartner Cool Vendor; backed by founders of HashiCorp and Slack). A decade running SRE, platform engineering, and DevOps teams across startups and global enterprises before that. KubeCon, theCUBE, and NYSE/ICE speaker.

  • Building Agents Since 2022
  • KubeCon · theCUBE · NYSE
  • Full-Stack Systems Architect

FOUNDED 2025 · SUNNYVALE, CA · OPERATING GLOBALLY

Reach us directly.

Both co-founders read every inbound. Expect a reply within one business day.

INFO@AGENTCYLABS.COM

+1 (877) 7-AGENTCY

SUNNYVALE, CA · OPERATING GLOBALLY