Enterprise AI Infrastructure — Now in Private Preview
Not Assembled.
Engineered.
The Reality
Not because the AI isn't smart enough. Because the infrastructure wasn't built for it. — Gartner
70% of engineering time goes to wiring frameworks to vector databases to monitoring tools to governance layers. Every integration boundary is a bug surface.
They ask reasonable questions: How do you prevent unauthorized API calls? How do you enforce spending limits? Can you halt mid-execution? Your team doesn't have good answers.
Ten engineers understand the pipeline. Compliance can't use it. Operations can't. Legal can't. Your AI investment serves ten people instead of ten thousand.
You didn't build a system. You assembled one. The seams between your framework and your vector database and your monitoring tool and your governance layer — those are where everything breaks. Governance gaps at the edges. Context lost in translation. An audit trail with holes.
You can't fix this with better integrations. You fix it with infrastructure where execution, governance, observability, memory, knowledge, and integration were designed together from the beginning.
Not assembled. Engineered. This is Forge.
Real screenshots from the Forge platform.
Chat, delegation tree, document intelligence, trace explorer — one governed environment.
Three creation paths: write a prompt, write code that delegates, or both with automatic fallback.
Natural language command interface to the entire platform. Intent to production in one sentence.
Egress rules, sandbox profiles, approval queues, budget caps — governance by architecture, not policy.
There is no ai.chat() in agent code. The bypass doesn't exist. The only path to AI reasoning routes through centralized model management.
The AI Assist panel is a natural language command interface to the entire platform. Create agents, configure workflows, manage knowledge — in one sentence.
Execution, governance, observability, memory, knowledge, tools, and integration — designed together from the beginning. No seams. No integration boundaries.
Everything you need to build, deploy, and govern AI agents in production — without assembling it from pieces.
Three creation paths: prompt-only, code-that-delegates, or both. Sandboxed QuickJS runtime. Agent-to-agent delegation.
Visual designer with branching, loops, parallel execution, and human-in-the-loop gates that actually halt.
Governed AI work environments with chat, files, delegation trees, computer sessions, and full execution ledgers.
Structured investigations with semi-autonomous workers, traceable findings, citations, and artifact generation.
Built-in OCR, format conversion, chunking, embedding, and vector retrieval. No external services required.
Cross-session recall, auto-capture, conversation summarization, and DLP safety policies.
Governance by architecture. Egress allowlists, validation policies, sandbox profiles, HITL approvals, budget caps.
171+ system tools. MCP client and server. OpenAPI spec import. Custom tool creation and API templates.
Natural language command interface to the entire platform. Context-aware across all screens.
Usage analytics, performance metrics, distributed tracing, per-execution billing and cost tracking.
$52B
AI agent market by 2030
171+
Built-in tools
72
Platform capabilities
18
Validation stages
Join the waitlist for early access to Forge.