The operating system for enterprise AI, with DevSecOps as the first use case
Argy sits between your teams, your toolchain, and LLM providers to govern AI usage, build AI apps and workflows, and industrialize DevSecOps through reusable modules and golden paths.
Explore next: automatable actions, use cases, why Platform Engineering.
Argy — the operating system for enterprise AI
Argy sits between teams, models, and the Your toolchain is your set of tools (Git, CI/CD, cloud, IaC, security). Argy doesn’t replace them: it orchestrates them and standardizes the experience.: an LLM Gateway for every request, governed agents, and An Argy module is a packaged golden path (config schema + implementation + guardrails). It turns your toolchain into governed self‑service. that industrialize A workflow is an orchestrated sequence of steps (e.g., provision → deploy → verify). Argy standardizes and observes flows to reduce cognitive load..
Argy is the enterprise AI OS: standardize once, govern all AI usage, and ship safely across In Argy, a product groups an application/service and its environments. It’s the unit where you apply modules, policies, and automations. and environments.
How Argy works
A product interface on top of your toolchain: the platform team defines the path, product teams consume in self-service, and governance stays built-in.
1. Standardize
Define golden paths
Ship a consumable capability: parameters, guardrails, documentation, and run readiness. Version it to evolve without forks.
2. Consume
Governed self-service
Developers pick the right path, fill a clear schema, and get a repeatable outcome (delivery + run) without ticketing.
3. Govern
Control, audit, continuous improvement
Policies, approvals, traceability, observability baselines: security and compliance become the default path—and adoption becomes measurable.
Go further: automatable actions, designing golden paths and consuming them as a developer.
Tenant configuration, made clear
Set identity, LLM providers, and notifications once—then scale with plan-based guardrails.
Identity
SSO + SCIM
Connect Azure AD, Okta, or Google Workspace. Sync users and roles per tenant.
AI
LLM providers & keys
Enable providers, generate keys, and enforce model policies per plan.
Alerts
Notifications
Route workflow events to Slack or Teams with real-time delivery.
Governance
RBAC & approvals
Apply roles, approval flows, and policy gates across modules and environments.
Launch
Publish the first path
Expose a golden path in the catalog, then onboard teams in minutes.
See the admin guide: tenant configuration.
A pragmatic rollout: weeks, not quarters
The goal is not to “rebuild a platform”. The goal is to ship a first standardized path, then expand with measurable adoption.
Week 1: scope & prioritization
- • Define first outcomes and pilot teams
- • Pick one critical workflow (provisioning, delivery, run)
- • Set standards (ownership, environments, rules)
Week 2: first golden path
- • Clear configuration schema
- • Guardrails by design
- • Docs and run baselines
Week 3: adoption & governance
- • Team onboarding
- • RBAC/SSO and traceability
- • Measure friction, iterate quickly
Week 4+: expand & optimize
- • Add new automations
- • Industrialize run ops (SRE baselines + runbooks)
- • Manage by outcomes (lead time, incidents, tickets)
What you get
An operating layer that speeds up delivery and structures run—without replacing your toolchain.
Faster provisioning
IaC baselines + versioned environments: less drift, more reproducibility.
Consistent delivery
Golden paths, CI/CD templates and quality gates per environment.
DevSecOps by default
Policies and checks embedded in the workflow instead of added at the end.
Run automation
Runbooks, incident routines, SLOs and observability baselines.
Measurable governance
RBAC/SSO, audit logs, versioned decisions—adoption and outcomes first.
Custom branding
Tenant name, logo, and portal domain customized for Growth+ plans.
Useful AI
Assistance and recommendations on workflows: diagnostics, choices, rationalization.
Built for demanding environments
Designed for large enterprises and fast‑growing scale‑ups.
Operational excellence
Governance, auditability, and adoption metrics included.
Standardization at scale
Reusable modules and reduced variability across teams.
Sovereignty & independence
EU hosting, on-prem LLM Gateway, and model-provider flexibility.
Is Argy right for you?
Perfect for
- Scale‑ups industrializing quickly.
- Enterprises modernizing their toolchain.
- Multi‑team, multi‑cloud organizations.
Not for
- Very small teams with no automation needs.
- Companies seeking a black‑box PaaS.
- Projects without standardization goals.
Trust & transparency
Technical depth and clear boundaries: what Argy does, and what it deliberately doesn't.
API-first (doesn't replace your tools)
Argy orchestrates your existing CI/CD, cloud and Kubernetes stack instead of becoming a new black box.
Open standards
Modules package proven building blocks: Terraform/Crossplane, GitHub/GitLab, OPA/Kyverno, observability baselines.
European SaaS
Procurement-friendly: GDPR posture, clear hosting assumptions, and enterprise-grade governance.
Governed AI Core
Argy's LLM Gateway is the unified entry point to LLMs, with routing, quotas, audit, and tenant-aware RAG (Retrieval-Augmented Generation) augments prompts with passages retrieved from your documents to deliver grounded, context-aware responses. on your internal knowledge.
- 1Complete AI governance: quotas, audit, filtering, and document RAG (Retrieval-Augmented Generation) augments prompts with passages retrieved from your documents to deliver grounded, context-aware responses..
- 2Multi-provider routing for vendor independence without client changes.
- 3Governed agents and assistants for real enterprise A workflow is an orchestrated sequence of steps (e.g., provision → deploy → verify). Argy standardizes and observes flows to reduce cognitive load..
- 4Contextual recommendations aligned to policies and scopes.
FAQ
Common questions.
Does Argy replace your existing tools?⌃
No. Argy interfaces with your toolchain (Git, CI/CD, cloud, Kubernetes, observability, secrets). Argy's role is to orchestrate and standardize via versioned modules, not to reinvent every brick.
What is an Argy 'module'?⌃
A module encapsulates an operational workflow: configuration schema, templates (IaC/CI), policies/guardrails, documentation, and runbooks. It is reusable, extensible, and applied per environment.
What is the difference with a 'home-grown' IDP?⌃
Argy provides a SaaS operating layer: catalog, governance, versioning, self-service experience, and steering. You keep your technical choices and tools — Argy accelerates standardization and adoption.
How to start in a few weeks?⌃
We start with 1 to 2 priority golden paths (e.g., microservice + ephemeral envs). Then, we expand the catalog and add governance/observability incrementally.
What is the role of AI in Argy?⌃
AI assists platform teams and developers in configuring modules, detecting drifts from standards (Golden Paths), and automated generation of operational runbooks.
Is Argy suitable for large enterprises?⌃
Absolutely. Argy was designed for scale, with fine-grained RBAC, SSO, audit logs, and dedicated support. It is the ultimate solution for organizations wanting to industrialize their DevSecOps.
European SaaS
GDPR compliant & hosted in EU
No Lock-in
Built on open standards
API-First
Everything is automatable
Ready to turn AI into an enterprise operating system?
Share your context (toolchain, constraints, org). We’ll propose a pragmatic rollout that makes AI governed, scalable, and sovereign.