SCOUT FOR CX

The AI coworker for support teams. It reads everything, and acts on it.

Ask Scout anything in plain language and it reads every ticket, review and thread, finds what's actually happening, and takes the next step: drafting the help article, filing the engineering ticket with the root cause attached, briefing product in the customer's own words. A person approves every change.

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KNOWLEDGE ATLAS

Your support team’s brain, connected to everything.

Knowledge Atlas is the knowledge base that writes itself - the source of truth powering Fini's agent and every surface your support runs on. Every resolved ticket becomes a cited article. Contradictions get caught before customers see them. Nobody spends their Friday updating docs

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Introducing SCOUT

One coworker, doing the job nobody on your team has hours for.

Ask anything in Slack

Reads tickets and public reviews

Custom reports from any source

Scheduled automations and alerts

Files tickets with root cause

Drafts help articles

Looks after your AI agent

Remembers what you teach it

The second job

Every support team has a second job. Nobody has the hours.

Read every ticket. And every review, thread and rating. Spot the pattern before it becomes a fire. Update the help center when answers are missing. Turn customer feedback into briefs and content. File the bug with evidence. Keep the AI agent sharp, and nobody has time to read it all.

So we gave that job to Scout.

HOW IT WORKS

How Scout works

Ask. Teach. Listen. Approve. Act. The loop your team runs every week.

ASK

Ask it like you'd ask a teammate.

Plain language, in Slack. No syntax, no dashboard, no query builder.

"What are customers angry about this week?", it reads every ticket and public review and comes back with the patterns.

"Why did the bot escalate this one?", it traces the conversation and tells you what went wrong.

Teach

Teach it once. It remembers forever.

Your experts correct Scout in the channel. No ticket to IT, no prompt engineering. This is the moment "coworker" stops being a metaphor.

"Always exclude our test tickets." "Verification issues are our highest severity." It holds onto that.

Every future answer, report and automation reflects what your team taught it.

Listen

It keeps watching between questions.

Tell it once to check something hourly and it does. Quiet while things are healthy, a ping the moment they aren't.

Monitors across every connected tool, not just when asked.

Scheduled reports land in Slack without anyone assembling them.

Approve

Nothing changes until you say so.

Scout reads freely. Anything that changes something is proposed and waits.

Every draft article, ticket and update lands as a proposal with an Approve button.

Every run is logged, every action scoped.

Act

Then it does the work.

The help article is written. The ticket is filed with the technical evidence attached. Product gets the customer's exact words, and the content drafted from them.

Files to Jira or Linear with linked customer reports and the root cause.

Drafts the help article, the product brief, and the marketing content.

REPORTS ON DEMAND

The report you never have to build. Or ask for twice.

Ask for any report in plain language and it arrives in minutes, in Slack or as a polished PDF. Then say "every Monday at 9" and it keeps arriving, forever.

Built with security and compliance embedded at every layer to protect sensitive financial data.

Top bugs this month, ranked by how many customers hit them.

What are customers angry about right now based on zendesk tickets and social media?

Every feature request from the last quarter, counted, with their exact words.

Where are the gaps in our knowledge base? What are people asking that we've never documented?

What are people saying about us on Reddit and Trustpilot this week, and is it getting worse?

Which issues are getting escalated to humans that the AI agent should be handling?

None of these are pre-built reports. None of them need to be.

1. You ask

2. You teach

3. It listens

4. You approve

5. It acts

We went from 15% to 70% automation on key journeys. Fini doesn't just follow our playbooks, it self-improves them

Crystal Stephens

Head of Operations, Atlas

We went from 15% to 70% automation on key journeys. Fini doesn't just follow our playbooks, it self-improves them

Crystal Stephens

Head of Operations, Atlas

Ask in plain language

No dashboard to build, no fields to configure, no analyst to brief. Any question, any source, in Slack.

Correct it once. Every report after respects it

"Exclude our test tickets." "Verification is highest severity." Said once, in the channel, and every report and digest that follows reflects it.

Turn any report into a standing automation

Say it once. It runs every Monday at 9, or every hour, or the moment a threshold trips, and it flags what grew since last week.

The fix arrives as a proposal

The drafted article, the filed ticket, the brief for product. Each lands with an Approve button and waits. Nothing changes until you click it.

One click, and the work is done

The article moves to your review flow, the ticket lands in Jira with the evidence attached, and product gets the customer's exact words.

1. You ask

2. You teach

3. It listens

4. You approve

5. It acts

We went from 15% to 70% automation on key journeys. Fini doesn't just follow our playbooks, it self-improves them

Crystal Stephens

Head of Operations, Atlas

Ask in plain language

No dashboard to build, no fields to configure, no analyst to brief. Any question, any source, in Slack.

Correct it once. Every report after respects it

"Exclude our test tickets." "Verification is highest severity." Said once, in the channel, and every report and digest that follows reflects it.

Turn any report into a standing automation

Say it once. It runs every Monday at 9, or every hour, or the moment a threshold trips, and it flags what grew since last week.

The fix arrives as a proposal

The drafted article, the filed ticket, the brief for product. Each lands with an Approve button and waits. Nothing changes until you click it.

One click, and the work is done

The article moves to your review flow, the ticket lands in Jira with the evidence attached, and product gets the customer's exact words.

TEACH IT ONCE

Your experts correct it once. It never forgets.

No prompt engineering. No ticket to IT. No admin console. The people who actually know your product tell Scout what matters, in the channel, in a sentence, and every answer, report and automation after that reflects it.

Correct it in the channel

"Always exclude our test tickets." "Verification issues are our highest severity." Said once, in Slack, by whoever knows.

It applies it everywhere

Every future report, query and scheduled digest respects what it was taught. You never repeat yourself.

It learns your team's shape

Who owns what, which accounts are enterprise, which customers are churn risks, how you like your reports formatted.

Ask it what it knows

"What have you learned about how we work?" It lists everything it is holding, and where each thing came from.

Try Knowledge Atlas for free

AGENT CARE

Somebody should be minding the bot.

You deployed an AI agent to answer your customers. Who checks its work? Scout tests your agent's answers against your knowledge base, traces exactly why a conversation escalated, finds the article or rule that was missing, and drafts the fix.

QA

QA

QA

Debug

Debug

Debug

Teach

Teach

Teach

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HOW SCOUT FITS WITH FINI

One AI talks to your customers. One works for your team.

Fini's support agent

Scout

Who it works for

Your customers

Your support team

Where it lives

Your help center, chat, email

Your team's Slack

What it does

Resolves customer questions autonomously

Reads, investigates, routes, and acts inside your company

Autonomy

Answers customers on its own

Proposes. A person approves every change

A support agent that waited for approval on every customer reply would be useless. A coworker that silently rewrote your help center would be unwelcome. Two jobs, two designs.

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PROVEN IN PRODUCTION

Teams are already using Scout and seeing great results

FASTER FROM CUSTOMER

SIGNAL TO SHIPPED FIX

0pt.

CSAT LIFT ON

RECURRING ISSUES

MORE CUSTOMER INSIGHT

REACHING PRODUCT

Atlas Safely Automated 70% of Key Fintech Support Journeys with FINI.

"We went from 15% to 70% automation on key journeys. Fini doesn't just follow our playbooks, it improves them."

— Crystal Stephens, Head of Operations

70%

Resolution Rate

<60 s

Avg Handle Time

Click to explore

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INTEGRATIONS

Your knowledge is scattered too. Scout reads all of it.

Half the institutional answer lives in an old Slack thread or a page nobody has opened in a year. Scout reads across every source at once, which is the thing no person can do.

Why CX teams use Scout

Compared to how this works today

Today

Scout

Finding what customers are saying

Open five tools, read for hours

One question in Slack, minutes

Building the weekly report

Export, pivot, paste, repeat

Ask once. It arrives every Monday

Asking a question nobody pre-built

File a request, wait for an analyst

Just ask. There is no schema to define

What the report covers

Whatever is in your helpdesk

Every connected tool, plus Reddit, X, Trustpilot, app stores

Public reviews and threads

Nobody has time to read them

Read and clustered with the tickets

Filing a bug to engineering

Copy paste, no evidence, days later

Filed with root cause and linked customers, in minutes

Telling product what customers want

A summary someone paraphrased

Their exact words, counted and sourced

Knowing your AI agent is wrong

You find out from a customer

Filed with root cause and linked customers, in minutes

QA'd, traced, and fixed before it repeats

Institutional knowledge

Trapped in old threads and docs

Filed with root cause and linked customers, in minutes

Read across every source at once

Getting better over time

Depends who is on shift

Teach it once, it remembers forever

Support teams already know what is wrong. Scout gives them the hours to do something about it.

Try Scout for free

Compliance First

Secure by design

Every Scout learns privately. Nothing it learns about your company is ever shared with another. Every action is scoped and every run is logged.

Built with security and compliance embedded at every layer to protect sensitive financial data.

SOC 2 Type II

PCI DSS Level 1

ISO 27001

GDPR

HIPAA · BAA-ready

Data Encryption

WEBINAR

See what Scout finds in a production support queue, live.

A working session on the second job every support team carries, and how Scout picks it up. Register now.

See it on your own support queue!

Book a call and we'll show you what Scout surfaces in your first week.

HOW IT WORKS

How Knowledge Atlas works

Live without engineering. Agentic workflows inside two weeks. Full autonomy by day 30. No migration project.

Disputes and fraud claims

Verify the customer, pull the transaction, and check it against your fraud rules before anyone is paged.

File the dispute, issue provisional credit where eligible, and log every step for the chargeback and audit trail.

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Account access and identity

Step up to KYC-grade verification before any sensitive action, every single time.

Reset MFA, unlock accounts, and re-verify identity within policy, no agent needed.

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Payments and transfers

Pull real-time payment, transfer, and payout status straight from your core systems.

Explain holds and failures, then trigger the retry or refund when your rules allow it.

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Start with what you already have.

Pulls from every source at once, no migration or cleanup first.

Merges overlapping docs so every answer has one home.

Bring in your help center, docs, PDFs, past tickets, and Slack threads. Atlas turns them into one structured tree of cited articles. No cleanup, no migration first.

Book a demo

Every resolved ticket becomes an article.

Extracts the information and updates the Knowledge graph

Files it in the right branch of your tree, searchable instantly.

When Fini hands a ticket to your team, Knowledge Atlas watches the resolution and writes the documentation, with no one touching a keyboard.

Book a demo

Two articles disagree. It catches it.

Flags duplicates, contradictions, outdated content, and version mismatches.

Surfaces them in a reconciliation dashboard, so there is no guessing what's current.

A contradiction in your docs becomes a contradiction in your AI's answers. Knowledge Atlas finds them before your customers do.

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Every answer traces to one source.

100% citation accuracy with full version history.

Confidence scores based on source reliability.

The tree structure is what makes the AI auditable: no blended answers from conflicting sources, ever.

Book a demo

Fini

READY

I don't recognize a $129 charge from Northgate Mart. I think my card's been used.

Confirmed it wasn't you. I've flagged the charge as fraud, filed the dispute, and posted a provisional credit while we investigate.

PROVISIONAL CREDIT +$129.00·CASE #FD-4471·ETA 1 BUSINESS DAY

identity.verify

Step-up auth · KYC

queued

ledger.lookup

Card ledger · last 30d

queued

fraud.evaluate

Risk engine · velocity

queued

dispute.file

Reg E · provisional

queued

One knowledge base. Every place support happens.

ONE SOURCE, EVERY SURFACE

Powers your AI agent

Clean, cited, conflict-free source data behind every answer it gives.

Hosts your help center

A branded, customer-facing center with AI search that deflects tickets before they arrive.

Reconciliation dashboard

Every conflict and gap in one place, with the current version flagged.

Version history

Full history on every article, so any answer is traceable to approved documentation.

Usage analytics

See which articles resolve, which gaps recur, and where search falls short.

130+ languages

Serve the same knowledge to customers in the language they ask in.

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SELF-LEARNING

It doesn't just answer. It learns.

Suggests new articles

Spots unresolved questions and drafts the missing coverage.

Suggests new articles

Spots unresolved questions and drafts the missing coverage.

Updates existing ones

Flags stale or conflicting articles and proposes the rewrite.

Updates existing ones

Flags stale or conflicting articles and proposes the rewrite.

Instructs per article

Writes usage rules on each article and refines them over time.

Instructs per article

Writes usage rules on each article and refines them over time.

Shows what's working

Analytics on which articles resolve and where gaps recur.

Shows what's working

Analytics on which articles resolve and where gaps recur.

RAGLESS SEARCH

No chunks, no embeddings. The LLM reads the actual article.

RAG retrieves fragments that sound similar and stitches them into blended, unsourced answers. Knowledge Atlas skips retrieval entirely: the LLM reads whole articles natively, understands what people actually mean, and traces every answer to one source.

"Card declined," "payment won't go through, one underlying issue, one right answer.

No retrieval layer to tune, no embeddings to re-index when docs change.

Search sharpens as it learns which articles actually resolve the query.

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Why CX teams use Knowledge Atlas

Compared to a traditional KB

Traditional knowledge base

Knowledge Atlas

Who writes the articles

Your team, by hand

Generated by AI from resolved tickets

Keeping it current

Manual, 15-20 hrs/week

Self-updating from live tickets

Conflicts and duplicates

Found by accident, if ever

Detected and flagged to reconcile

Chunk retrieval (RAG)

LLM native AI search (RAGless)

Answer sourcing

Blended from several articles

One cited, authoritative article

Customer-facing help center

A separate tool

Built in, hostable, same source

Gets better over time

Traditional tools help you search what you already wrote. Knowledge Atlas writes it, fixes it, and keeps it honest.

Try Knowledge Atlas for free