One platform. Every piece
of your agentic stack.
Context, governance and execution in one platform. It all starts from the Context Catalog, which every app and orchestrator reads and writes.
- Allianz
- ATM
- Aviitam
- Cattolica
- CNH
- Concrete
- Confindustria Dispositivi Medici
- Coop Etruria
- Coop.fi
- Crif
- Eolo
- Flex
- Gruppo Villa Maria
- HDI Assicurazioni
- Helvetia
- IIT
- Italo
- MD Concierge
- N-AND Group
- NeN
- Primo Caredent Group
- Quixa
- RBdigital
- Trenord
- Trieste Trasporti
- Unicoop Firenze
- Unicoop Tirreno
- Vodafone
- Youhealthy
How it all connects.
One Context Catalog underneath everything, from your first agent to your existing infrastructure.
1Tools and outputs the business relies on
Business applications
2What do they build in?
Own Coding Tools
Software Engineers
Flow
Browser workspace, plain language
Non-developers3Where do the rules, AI templates and guidelines live?
AI Foundry
Matches each request to the AI Playbook and selects the most applicable AI agent to execute the task through the relevant list of skills
DevOps / Platform Team4What gives the AI its context?
Context Catalog
The map the AI reads: every app, API, dataset, team and rule
DevOps / Platform Team5What orchestrates or facilitates integration?
Platform Orchestrator
6Existing tools and systems
Customer's existing IT
Our Apps built on Context Catalog
Everything here reads from and writes to the same source of truth.
Context Catalog
The governed record of your organization: every agent, system and team working from the same verified source, kept in sync and continuously improved through engineering intelligence (scorecards and campaigns).
AI Foundry
Governs AI Playbooks: pre-configured agentic workflows with a fixed model, skills and MCP tools, validated before execution. Federates and governs MCP servers, with observability and token optimization built in.
Connect it to what you already run.
3 Platform Orchestrators bring Context Catalog to your existing environments, Data and APIs.
Governance Built In.
Policy, access and audit, part of the platform, not bolted on afterward.
Policy Enforcement
Guardrails enforced via MCP Gateway (owned by AI Foundry), hard boundaries on AI Act, GDPR and SOC before output ever reaches a human.
Access Control
RBAC through the deterministic "Rules, Permissions, Relationships" layer in Context Catalog.
Compliance Policies
The non-deterministic policy layer maps to NIS2, DORA and AI Act, with pre-built Scorecard Templates for each.
Audit Trail
Item Versioning and an Audit Log on every catalog change, for provable, reviewable compliance.
Mia-Platform and the alternatives.
Eight categories you may be weighing, on two questions: does it enforce rules where AI runs, and does it work with any agent, model and cloud? Open one for the full comparison.
- 1Internal Developer Platforms & Portals
- 2DevOps Platforms
- 3AI & MCP Gateways
- 4Hyperscaler Agent Platforms
- 5Build In-House (not a market: it can land anywhere)
- 6Developer Productivity Insight Platforms
- 7AI Governance Platforms
- 8AI Cost & FinOps Tools
Positions are indicative and based on public documentation. Categories are broad and individual products vary. Build In-House is an approach, not a market category, so it can sit anywhere on the map.
Frequently Asked Questions
No. It complements them: it doesn't replace coding assistants, CI/CD or systems of record, and it doesn't replace Governance, Risk & Compliance (GRC) tools used for policy management and risk registers. It enforces those policies at the point where agents act.