AI made coding 5x faster.Your release pipeline didn't.
Cursor, Copilot, and custom agents can generate change. Facets gives them the organizational context, guardrails, and orchestration layer to deliver that change safely.
Trusted by platform teams at enterprise scale
Engineering leaders standardizing delivery before adding AI to the change path.
AI agents alone cannot understand your SDLC
They can write code, Terraform, and runbooks. They still need a live model of environments, policies, dependencies, and release order before they can act in production.
Agent + Existing Pipelines
Fast generation, slow delivery
- No shared knowledge graph across code, infra, environments, and policies.
- Change order lives in tickets, tribal memory, and fragile pipeline glue.
- Every agent needs human review to understand blast radius and compliance.
- More generated change creates more operational coordination.
Agent + Facets Orchestrator
Fast generation, governed execution
- Agents reason over approved blueprints, modules, environments, and ownership.
- Every change flows through one system of change with dependency awareness.
- Policy, cost, security, and compliance checks are enforced before execution.
- Developers get self-service outcomes without bypassing platform guardrails.
From agent output to governed delivery
Facets connects what AI tools generate to what your delivery stack can safely execute.
Agents generate change
Cursor, Copilot, and custom agents produce code, Terraform, runbooks, and configuration from developer intent.
Facets applies context
The orchestrator maps each change to your blueprints, ownership model, environment topology, and active policies.
Change is sequenced
Dependency ordering, approval gates, and release scheduling are resolved before anything touches production.
Self-service outcome
Developers get what they need without opening tickets or bypassing platform guardrails.
Agents generate change
Cursor, Copilot, and custom agents produce code, Terraform, runbooks, and configuration from developer intent.
Facets applies context
The orchestrator maps each change to your blueprints, ownership model, environment topology, and active policies.
Change is sequenced
Dependency ordering, approval gates, and release scheduling are resolved before anything touches production.
Self-service outcome
Developers get what they need without opening tickets or bypassing platform guardrails.
The AI Orchestrator for Software Delivery
Facets sits between AI tools and your delivery stack — as both knowledge graph and system of change.
Facets AI OrchestratorThe Three-Layer Solution
Building AI-native SDLC the right way
The Tools
You already have this today!
The Orchestrator
The orchestrator builds the organization context through contracts
The AI Agent Layer
The context powers the AI Agents. Agents drive changes through the orchestrator.
Ask. Orchestrate. Deliver.
The Facets AI Assistant understands your entire SDLC — not just the code. Watch it correlate deployment history, environment state, and service ownership in real time.
What the orchestrator knows
Every query is answered against a live knowledge graph of your delivery stack.
What the agent can do
Debug an incident in seconds
Three agents that become useful with orchestration
Not another chatbot. Agents with enough delivery context to recommend, compose, and execute changes inside your guardrails.
“We've avoided many potential issues with Facets. Proactive reliability approach significantly improved our operational stability.”
Pruthvi Narapareddy
Director of Engineering
Debug incidents with full SDLC context
Correlates incidents across services, environments, infrastructure, deployment history, and observability signals — all from the same knowledge graph.
- Reduces time spent manually joining signals
- Finds likely infra and release root causes faster
- Escalates with context, not screenshots
Meet the AI Agents
Creating Productivity Impact in Software Delivery
Meet the AI Agents
Creating Productivity Impact in Software Delivery
Debugging Agent
AI agent to help you debug issues by correlating issues across services and infra
- 60% reduction in MTTR
Terraform Authoring
Author new Terraform modules following organization standards and contracts
- 10 mins to author, 100% compliant
Blueprint Designer
Design Blueprints for the developer use-case using pre-approved modules developed by Platform Teams
- 5X faster provisioning, Zero ticketOps
What your AI agents need to know
Facets maintains the delivery context that generic coding tools do not have: what exists, what is allowed, what depends on what, and how change should flow.
Service Architecture
Dependencies, ownership, runtime topology, and communication patterns across services.
Environment Topology
Configuration, promotion paths, cloud accounts, clusters, and environment-specific variation.
Deployment Patterns
Release order, rollback needs, approval gates, and historical delivery behavior.
Cost Attribution
Team, project, environment, and resource-level cost ownership for smarter FinOps action.
Security Posture
Policy, compliance, secrets, permissions, and governance rules enforced before execution.
Performance Signals
Resource utilization, scaling patterns, incident history, and operational health signals.
Recognized by Gartner for AI-assisted infrastructure delivery
Facets is named in the Gartner® Market Guide for AI Assistants for Infrastructure as Code, 2026.
Analyst Recognition
Listed as a Representative Vendor with Facets Intelligence, recognized for contextually grounded, policy-enforcing, agentic IaC capabilities.
Referenced in Gartner's Reference Architecture Brief for Infrastructure Platform Engineering.
Gartner® Hype Cycle™ for Platform Engineering, 2025
Included as a Sample Vendor for Self-Service Environment Management category.
Acknowledged in Self-Service Environment Management category.
Listed as a representative vendor providing infrastructure automation and orchestration capabilities.
Gartner® Hype Cycle™ for Platform Engineering, 2024
Mentioned in the Self-Service Environment Management category as a Sample Vendor.
Hype Cycle for Site Reliability Engineering, 2024
Facets is mentioned in the context of platform engineering and infrastructure automation capabilities.
AI x Platform Engineering Impact
“We empowered teams with workflow ownership using Facets. Developer autonomy transformed our entire delivery process and everything clicked perfectly.”Read Case Study
Kaushal Bagtharia
AVP, DevOps · MPL
Bring your own agents to the Facets Orchestrator
Let AI generate change without letting it bypass your platform standards, policies, and delivery order.