The governed platform for enterprise AI agents and AI applications.
Gaia is the governed platform for building, operating, and scaling enterprise AI agents and AI applications. It turns agents into an operable enterprise capability by connecting design intent, runtime orchestration, working artifacts, governance, and continuous delivery.
It is not just an agent builder, copilot surface, or orchestration layer. Gaia keeps runtime control, evals, dashboards, delivery evidence, and governance records inside one control plane.
A governed platform for enterprise AI agents and AI applications instead of a stitched-together AI toolchain.
Clearer continuity between design intent, agent runtime execution, evidence, and release decisions.
Shared governance and operational evidence across teams, applications, and providers without duplicating control logic.
Most AI stacks leave a lifecycle gap.
Teams can assemble pilots quickly, but enterprise AI gets harder when search, copilots, evals, workflow automation, dashboards, and governance records live in different systems owned by different teams.
- Controls live outside the agent runtime and delivery workflow
- Standardization still happens project by project
- Execution evidence and control logic become fragmented
- Ownership breaks across design, runtime, and release
- Shared controls across teams and applications
- A clearer path from pilot to governed production operations
The platform carries the work itself, not just the controls around it.
The same six surfaces make Gaia concrete across design, execution, evaluation, and release: governance, conversation work, document context, workflow topology, evaluation, and delivery management.
- Inspect linked records across runtime, risk, evidence, and discovery.
- Keep governance review attached to operational queues instead of separate trackers.
- Keep working outputs tied to the conversation context and revision history.
- Promote reusable outputs into delivery evidence without switching tools.
- Combine files, search, and grounded retrieval in one shared workspace.
- Preserve access boundaries while keeping evidence sets aligned across the team.
- Keep automation topology inspectable from design through workflow runs.
- Review process structure without reverse-engineering it from code or logs.
- Track regression signals and readiness without exporting the workflow to another eval stack.
- Keep quality evidence close to the configurations and releases it informs.
- Connect delivery work to artifacts, evaluations, and release decisions.
- Make rollout readiness visible without stitching together separate project tools.
One operating model across design, execution, and evolution.
Gaia is designed to keep business intent, technical execution, and governance evidence connected instead of scattering them across separate systems.
Capture roles, workflows, data boundaries, artifact templates, and governance expectations as assets that stay active in the same operating system after launch.
Coordinate agents, tools, models, document folders, and graph-based workflows with explicit control over execution and evidence instead of scattering them across separate products.
Use evaluation, auditability, artifact history, and delivery process signals in the same system that informs readiness, change decisions, and rollout evolution.
A repeatable path from agent design to governed production.
Gaia gives platform and delivery leaders a single rhythm for launching, monitoring, supervising, and improving enterprise AI agents and AI applications.
Step 1
Design with governance in view
Define how the application should behave, what it can access, who owns it, and how the operating model should work before scale creates drift.
Step 2
Run with governed orchestration
Connect agents, tools, channels, and context through one runtime model that preserves control instead of scattering it across integrations.
Step 3
Evaluate continuously
Review quality, safety, and operational signals in the same platform used to design and operate the application.
Step 4
Deliver and evolve with discipline
Move changes through a repeatable delivery process with explicit evidence, ownership, and release decisions.
What this changes operationally
The platform is built to make governed agent operations easier to govern, easier to scale, and easier to improve.
A governed platform for enterprise AI agents and AI applications instead of a stitched-together AI toolchain.
Clearer continuity between design intent, agent runtime execution, evidence, and release decisions.
Shared governance and operational evidence across teams, applications, and providers without duplicating control logic.
Less recurring integration work as new use cases, workflows, and business units come online.
See the platform beyond the narrative.
Use the resources below to inspect how Gaia is documented, operated, and explored in practice.
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Explore tutorialsBuild the control plane before agent sprawl sets in.
Gaia helps platform leaders move from isolated agent pilots to governed enterprise AI operations with a clearer architecture, clearer controls, and clearer evidence.