AI search for your documentation
The fastest way to give your docs an answer engine is a managed widget: Achla AI crawls your documentation and help center and returns a direct, cited answer to each question — in the visitor's own language — for a flat $15 or $39 per month, with no backend to run and no LLM key to manage. Instead of handing readers a list of pages to skim, it reads the relevant docs for them, writes the exact step, and links the sources, so your team stops answering the same question over and over.
Updated 11 July 2026
Achla AI vs classic documentation search
| Capability | Achla AI | Classic docs search |
|---|---|---|
| What the reader gets | A written answer grounded in your docs, with citations | A ranked list of pages to open and skim |
| Complex content | Indexes PDFs and complex pages the native search misses | Usually keyword match on page text only |
| Setup | One script tag; built-in crawler; no backend | Built into the docs platform or self-hosted index |
| Languages | 8 languages incl. RTL; answers in the reader's language | Typically the docs' own language only |
| Pricing | Flat $15/$39 per month, fixed query volume | Varies; often per-seat or per-request at scale |
Why do answers beat keyword search for docs?
Readers arriving at your documentation have a specific question — how to configure a setting, why an error appears, which endpoint to call — and a keyword box makes them guess terms, open several pages, and hunt for the one relevant sentence. An answer engine reads the relevant pages for them and writes the exact step, then shows which documents it used so the answer is verifiable. That is the difference between finding pages and getting an answer, and for support-heavy docs it is what keeps a reader from giving up and opening a ticket instead.
Can it reduce support tickets?
That is the core use case: deflecting repetitive questions before they reach your inbox. When the answer to a common question is one search away and grounded in your own docs, many readers self-serve instead of writing in. The industry reports meaningful ticket-deflection rates from AI answer layers on documentation — vendors cite figures across a wide range — and while your own result depends on your docs and traffic, the mechanism is straightforward: stop answering the same question over and over by letting the docs answer it directly. We would rather point you at the industry's reported ranges than promise a specific number we cannot guarantee for your site.
Are the answers grounded in my documentation?
Yes — grounding is enforced, not optional. Every answer is built from your indexed documentation and carries citations to the pages it used, and when your docs do not actually contain an answer, Achla declines rather than inventing one. That matters for documentation, where a confidently wrong answer is worse than no answer: a reader who is told the wrong flag or the wrong endpoint loses trust and files a ticket anyway. Because each reply links its sources, readers can click through and confirm, and your team can see exactly which pages an answer came from.
Does it handle PDFs and complex docs?
Yes. Achla's crawler reads your HTML docs and also extracts text from PDFs and documents, so reference material that native docs search cannot reach — a downloadable spec, a compliance PDF, a dense reference table — becomes answerable. Setup is turnkey: point Achla at your docs, it crawls and indexes them, keeps the index fresh as you publish, and serves the widget. There is no search backend to stand up, no embeddings pipeline to maintain, and no separate model key to wire in.
When is a sales-led tool the better fit?
We aim Achla at small and mid-size teams that want a turnkey, cited answer layer on their docs without an enterprise contract. If you run very large developer documentation with bespoke needs — deep integrations across many products, custom ingestion, or dedicated relevance tuning — sales-led specialists like Kapa.ai or Inkeep are built for exactly that and are worth talking to. Achla's advantage is the opposite end: a flat, predictable price, a one-line install, answers in the visitor's language, and citations by default, with no procurement cycle to start.
FAQ
- Does it work with any documentation site?
- Yes. Achla crawls your public docs or help center — whatever platform they run on — indexes them, and serves the widget. There is no backend to build.
- Will it invent answers when my docs don't cover something?
- No. Answers are grounded in your indexed docs and cite their sources; when the docs don't contain an answer, Achla declines instead of guessing.
- Can it answer in my readers' languages?
- Yes. Achla supports 8 languages including right-to-left Hebrew and Arabic, and answers each reader in their own language by default.
- How much does it cost?
- A flat $15 or $39 per month with a fixed included query volume, so the bill is predictable and overage is capped.
Give your docs an answer engine
Install one script tag, let Achla crawl your documentation, and start deflecting repeat questions with cited answers — for a fixed $15/month.