LangGraph is a well-designed framework for developers building bespoke agent systems. Findable is the platform an enterprise runs those systems on. This page is the honest comparison — including when LangGraph is the right choice.
The short version: a framework hands you the interesting 5% of an agentic system and leaves you the mandatory 95% — execution infrastructure, governance, human checkpoints, integrations, and an interface non-engineers can operate. Findable ships that 95% as a product that deploys inside your own Azure tenant.
LangGraph: code-only graphs — every workflow is an engineering artifact.
Findable: a visual Flow Designer with 14 node types, 55 built-in flows, and AI generation from a plain-English description. Teams that own the workflow can read and change it.
LangGraph: you build the runtime — checkpointing, retries, observability are your platform team's job.
Findable: a graph-walker engine with checkpoint persistence, crash recovery, and token-level execution tracking, out of the box.
LangGraph: interrupt/resume primitives — the mechanism, not the loop.
Findable: structured forms with 17 field types, routed to users or Azure AD groups, majority-vote and sequential strategies, delivered natively in Slack and Teams.
LangGraph: custom build on top of stores you assemble.
Findable: Mem0-backed memory with six scopes, admin-controlled retention and compliance locks, per-chat scope selection.
LangGraph: whatever you wire up via LangChain and custom code.
Findable: ~250 pre-configured — 15 LLM providers, 27 databases queryable in plain English, 44 MCP servers, 170+ built-in tools, 16 vector stores.
LangGraph: a library — security posture is whatever surrounds it.
Findable: runs inside your Azure tenant with Entra ID SSO, RBAC with inheritance, full audit trails, and zero data egress by architecture.
If you have a dedicated engineering team, a single high-value use case, and requirements too unusual for any platform's abstractions, building on LangGraph is reasonable — framework flexibility is real. The trap is subtler: committing, one workflow at a time, to building a platform you never planned to own. If your goal is many workflows, owned by business teams, governed centrally, and live this quarter, you're describing a platform.
The longer analysis is in our essay Beyond LangGraph: What Enterprise AI Workflows Actually Need, and the broader evaluation checklist in Enterprise Agentic AI: The Complete Guide.
Findable deploys inside your Azure tenant in under a week — your identity, your storage, your audit trail. Request a demo or explore the Flow Designer.