> ## Documentation Index
> Fetch the complete documentation index at: https://docs.enfors.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Welcome to Enfors
> AI Workforce Intelligence Platform for AI agents and the humans behind them.
**Enfors gives you one place to see what your AI workforce — people and agents — is actually
doing, deciding, and costing.** You see what's being built,
how every decision gets made, where the spend goes, and where the same work is being done
over and over. Spot trouble before your customers do — an agent drifting, a decision going
wrong, effort duplicated across teams — cut the waste, and measure the real return on
every dollar of AI.
## Two kinds of intelligence
Enfors is organized around two intelligences, both running on **one captured source of
truth** — every agent, session, artifact, and decision captured automatically from your
gateway.
*What your workforce produced — and the hard ROI on it.* Day-one value for engineering,
AI, and finance leadership: who built what, what it cost, and whether it was worth it.
*Every decision, provable and defensible.* Value at scale for risk, compliance, and
agent owners: how each decision was reached, with the evidence to back it.
See [Use cases](/getting-started/use-cases) for where each pays for itself.
## The three pillars
Enfors is built to answer three questions about your AI workforce:
Every agent and person in your workspace, their sessions, and the work they
produce — grouped automatically into Features and Epics.
Every decision reconstructed into a logic trace, backed by evidence, with
outcomes, quality scores, and drift detection.
Spend per agent, per session, per shipped value — the basis for the cost
conversation you couldn't have before.
**Agent-agnostic, model-agnostic, privacy-respecting.** Enfors works with the agents you
build, the coding assistants your developers use, and third-party agents you adopt — across
Anthropic, OpenAI, Gemini, Bedrock, Azure, or your own deployment. Your data stays in your
environment, and Enfors never trains on customer traffic.
## Two lenses, one platform
The same data serves two very different people:
The macro picture: *what is my AI workforce doing and costing?* Live workspace
status, Pulse reports, and natural-language queries — no dashboards to build.
The micro picture: *why did this one agent do what it did?* Explore the canvas,
walk a session's decisions, open the logic trace and evidence vault.
## Start here
Connect your first agent in a few minutes with the macOS gateway installer.
The architecture: gateway → decision ledger → graph → product surfaces.
The decision ledger, evidence model, insights, and ROI tracking explained.
Query Enfors from Claude Code, Cursor, or your own tools.