Fini (usefini.com) is an AI agent for customer support that resolves tickets across chat, email and voice in 130+ languages, takes actions in your systems, and maintains its own knowledge base. It is built for regulated industries (fintech, banking, insurance, healthcare) and runs on top of the helpdesk you already use, so there is no migration: a knowledge agent is live on day 1, agentic workflows by day 14, and full autonomy by day 30. This page is the plain explanation of what Fini is and what it does. If you already know and want a map of the docs, start at the Introduction. If you want the mechanics of a single conversation, read How Fini works.

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Who Fini is for

Fini is used by support teams that handle a high volume of customer conversations and can’t afford a wrong answer. Fini’s customer base skews toward fintech, banking, insurance and healthcare, where every reply can carry a regulatory, financial or clinical consequence and audit requirements are non-negotiable. Three groups inside a customer typically work with Fini:

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What Fini does

Fini does four jobs. Each one maps to a part of the product you configure.

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1. Answers questions from approved knowledge

Fini answers from Articles, the curated knowledge graph that is the single source of truth for every agent. Raw content (help center pages, files, Notion, Google Drive, Confluence, Zendesk Help Center) enters through Sources, becomes candidate knowledge, and only reaches Articles after it passes the review and publish workflow. Retrieval is RAGless: the agent reads whole approved articles rather than fragments stitched together from a vector index. See the Knowledge overview.

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2. Takes actions in your systems

Fini doesn’t stop at telling a customer what the policy is. With Actions it can call your APIs mid-conversation (cancel a subscription, look up an order, update an address, reorder a card), and with Attributes it pulls in the customer’s plan, account state or recent orders so the reply is about this customer. Multi-step workflows such as refunds, cancellations or identity checks are built in the Rulebook as behavior trees that run deterministically: the same inputs produce the same path every time.

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3. Keeps its own knowledge up to date

Fini watches the conversations it handles and proposes improvements. A background AI pass detects gaps (questions no article answers) and conflicts (two inputs that disagree) and drafts a fix. Magic Articles turns raw content or a resolved conversation into a structured article. Drafts from the background AI always land in Review and never publish without a human approving them; for Magic Articles, Status After Generation decides whether a draft goes to Review or straight to Published.

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4. Escalates to your team when it should

When a conversation needs a person (by policy, because a check failed, or because the customer asked) Fini hands it to your human team with the conversation, the knowledge it used and its reasoning trace attached. You decide what triggers a handoff: escalation topics in the Planning Prompt, Rulebook branches, Guardrails that can’t produce a safe reply, and Reply Rules that keep the agent silent or internal-only on sensitive intents. The four jobs connect into one loop: approved knowledge and your systems feed the agent, the agent replies or hands off, and what it learns from conversations comes back to your team as drafts to approve.

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Where Fini runs

Fini is headless. The same agent, with the same knowledge and rules, can answer on several surfaces at once. The full list, including the Chrome extension and cards for Discord, Freshdesk and Deskpro, is on the Channel overview.

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The four aspects of an agent

Every agent in Fini has four aspects. You configure each one independently and they compose into one running agent. One workspace can run many agents, for example one for billing, one for onboarding and one for internal IT, each with its own knowledge scope, rules and deployments.

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Headline facts

To confirm (internal, remove before publish): www.usefini.com/trust-metrics lists “resolution accuracy (95%)” while the homepage and llms.txt say 99% accuracy. Which accuracy figure should the docs state, and how is each defined?

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What Fini is not

  • Not a helpdesk you migrate to. Fini runs on top of Zendesk, Intercom, Salesforce and the other helpdesks it integrates with. Your tickets, macros, queues and human team stay where they are; Fini reads and replies inside them. Teams that want inbound email without a third-party helpdesk can use Fini’s native Email channel, which routes into the Inbox ticket workspace. See Fini on top of your helpdesk.
  • Not a free-running chatbot. In the Rulebook, the LLM works only inside behavior tree nodes (Check, Read, Reply, Form) and a deterministic tree walker decides which node runs when. Per-agent Guardrails check generated replies before delivery.
  • Not a black box. Every reply has an AI Steps trace: planning, the attributes it loaded, the rule it ran, how it composed the answer, the tags it applied and the guardrail verdicts.
  • Not a model trained on your data. Customer data is never used to train foundation models.
  • Not self-publishing. Knowledge changes Fini proposes on its own (gaps, conflicts, Refine with AI drafts) wait for your team to approve them.

How Fini works

The lifecycle of one conversation, from arrival to escalation and self-improvement.

Quickstart

Create an agent, add knowledge, deploy in shadow mode, and iterate.

Rollout timeline

What happens on day 1, day 14 and day 30, and what your team does at each step.

Fini FAQ

Short answers to the questions teams ask most about Fini.