KB READY / AGENCY LAUNCH QA

White-label launch QA for AI support agencies.

KB Ready is researching the repeated go-live work agencies still do by hand before Intercom Fin, Zendesk AI, or custom RAG support bots are safe to ship.

Not general chatbot strategy. The focus is the last-mile launch work: source cleanup, structure fixes, knowledge gaps, answer boundaries, multilingual breakpoints, and starter eval coverage.

If your team owns launch quality for client AI support rollouts, I want to learn what still happens manually today.

Share your workflow See the launch QA pack

No call required
2-minute survey
For agencies shipping repeated Fin or Zendesk launches

Research note: survey responses are used for validation and optional follow-up only. Please do not send client documents or confidential exports through this form.

The last-mile work

Where launches still break

The repeated patterns I keep seeing when agencies ship Fin, Zendesk AI, or custom RAG support bots for clients.

Source sprawl

Conflicting PDFs, help-center articles, Notion pages, and policy docs hide the real answer set.

Weak answer boundaries

Bots launch without clear escalation notes, exclusions, or risky edge cases called out.

Multilingual drift

Translated content looks complete but breaks first when structure and meaning diverge.

No repeatable QA

Agencies still improvise launch checks instead of using a consistent backend workflow.

Who this is for

Built for agencies shipping repeated launches

Agencies shipping repeated Intercom Fin or Zendesk AI launches

Consultants who own go-live quality for client support bots

Teams that need a white-label backend, not another software platform

The first launch QA pack

What the first launch QA pack may include

A white-label backend for the last-mile work agencies are already doing by hand on every client launch.

Source audit and normalization notes

A structured read of the client's docs: what is canonical, what is duplicated, what should be dropped before ingestion.

Structured source pack

A clean, chunk-ready set of source files in a consistent shape, ready for Fin, Zendesk AI, or a custom RAG pipeline.

Gap and contradiction review

Flagged gaps, conflicting policies, and ambiguous answers across the client's knowledge base before they ship as bot replies.

Answer-boundary and escalation guidance

Explicit notes on what the bot should answer, where to refuse, and which edge cases must escalate to a human.

Multilingual risk review

A pass over translated content to flag where structure, meaning, or coverage diverges from the source language.

Starter eval set

A small, launch-focused test set so agencies can defend go-live quality with evidence instead of vibes.

Example structure

Illustrative launch QA pack

Source audit, gap review, answer boundaries, multilingual risks, and starter eval coverage for one client rollout. Structure only — not a real client deliverable.

/acme-launch-qa-pack/

Illustrative · not a real client

01-source-audit.md

Source audit

Inventory of client docs, canonical vs duplicate vs obsolete, and what should never reach the bot.

02-gap-review.md

Gap & contradiction review

Missing answers, conflicting policies, and ambiguous phrasing flagged before go-live.

03-answer-boundaries.md

Answer-boundary notes

What the bot should answer, where to refuse, and which questions must escalate to a human.

04-multilingual-risks.md

Multilingual risk notes

Where translated content diverges from the source in structure, coverage, or meaning.

05-starter-evals.jsonl

Starter eval set

A small, launch-focused question set the agency can run before and after go-live.

06-handoff-checklist.md

Handoff checklist

The white-label handoff: what the agency ships to the client on launch day.

Want to see the structure evolve into a redacted real sample as pilots come in? Share your workflow and I will send the next version when it is ready.

Share your workflow Request the sample pack

Short FAQ

Common questions

Are you selling software today?

No. This is a validation study for a narrow, agency-facing service layer.

Will you ask for a call?

No call is required. Survey first. I will only follow up if you ask to see a sample pack or hear about the pilot.

What might the eventual offer look like?

A white-label launch QA pack for agency-led support bot rollouts: source cleanup, structure notes, gap flags, answer-boundary guidance, multilingual risk review, and a starter eval set.

Run by

Farshid Pourlatifi

Researching launch QA for AI support agencies.

linkedin.com/in/farshidpourlatifi