Ragable · RAG Platform

AI chatbots grounded in your own documents.

Ragable indexes your PDFs, manuals, policies and FAQs into searchable knowledge bases, then answers questions from them and cites the source. Deploy it as a JavaScript widget, inside your app, or on your own infrastructure.

Source-groundedJS widgetPopular doc formatsCloud or on-premise
app.ragable.eu / workspace · acme-eu
BotsKnowledgeConversationsUsage

Knowledge bases

Product docs · EU
184 documentsupdated 2h ago
1.2M tokens
indexed
Support FAQ
52 documentsupdated yesterday
318K tokens
indexed
Legal & policies
23 documentsprocessing 6 of 23
-
processing
Engineering handbook
97 documentsupdated 3d ago
740K tokens
indexed
R
Acme Assistant
online · grounded in 4 bases
What's the refund window for annual plans?
Annual plans can be refunded within 30 days of purchase. Pro-rated refunds apply after that window only for service incidents.
pricing-policy.docxbilling-faq.md
Ask anything…
How it works

Four steps from a folder of documents to a grounded AI assistant.

Ragable handles ingestion, retrieval and grounded generation, so what you ship is a chatbot that answers from your sources instead of another demo.

Step 01

Upload your knowledge

Bring in PDFs, documents, spreadsheets, manuals, policies, FAQs and internal files. Ragable indexes them into searchable knowledge bases, scanned pages included.

PDF · DOCX · MD · CSV · HTML · TXT
Step 02

Configure your assistant

Pick a knowledge base, set the behaviour, choose the AI model, decide which tools it may use and set the limits it runs under.

system prompt · model · tools
Step 03

Deploy anywhere

Embed the chatbot with one line of JavaScript, call it from your application, or run conversations straight from the Ragable panel.

<script src="…/ragable.js"></script>
Step 04

Scale securely

Start on SaaS, then move to private cloud or on-premise infrastructure when security, compliance or integration requirements grow.

SaaS → Private cloud → On-prem
Two tracks, one platform

Built for both self-service teams and enterprise deployments.

Start on SaaS in an afternoon. Move to private or on-premise infrastructure when your security, scale or integration needs grow, without rewriting your assistant.

SaaS · self-service

Start fast with SaaS.

For growing teams that want a grounded assistant in front of users this week, not next quarter.

  • Plans from $99/month
  • Upload documents, build knowledge bases in minutes
  • Embed chatbot widgets with a one-line JavaScript snippet
  • Use leading cloud AI models out of the box
  • Manage assistants, sources, and conversations from a clean dashboard
  • Plan-based session and token limits with usage analytics
View pricing From $99/mo
Enterprise · on-premise

Deploy on your own terms.

For organizations with stricter requirements: private clouds, isolated infra, custom models, and security review.

  • Custom RAG architecture tuned to your data
  • On-premise or private cloud deployment
  • Custom model providers: open-source, hosted or your own
  • Isolated infrastructure with security review
  • Dedicated integrations with internal systems
  • Custom limits, SLAs and named support
Request consultation Custom pricing
Product

The platform layer between your knowledge and the AI that uses it.

Ingestion, retrieval, orchestration and the interface on top, built for teams that need answers tied to real sources.

Knowledge base management

Create multiple knowledge bases per team, product, client, or internal process.

Document indexing

Index popular document types and turn static files into searchable, AI-ready context.

RAG engine

Retrieve the right passages first, generate second, so every answer stays tied to your real content.

Embeddable widget

Add a production-ready chatbot to any site or app with a single JavaScript snippet.

Built-in user panel

Manage assistants, knowledge bases, sessions, and conversations from one clean dashboard.

Multi-model AI support

Use leading cloud models today, swap to custom or self-hosted providers tomorrow.

Enterprise deployment

On-premise, private cloud, isolated environments, and security review on request.

Limits & packages

Control cost and risk with plan-based limits for sessions, tokens and usage volume.

Use cases

From customer-facing chat to private document intelligence.

RAG fits anywhere people currently search through documents. They ask a question instead, and get a grounded answer with its sources.

01 · Support

Customer support AI

Answer customer questions from your documentation, FAQs, policies and product manuals, with a citation to the page each answer came from.

Learn more
02 · Internal

Internal knowledge assistant

Help employees find answers across procedures, onboarding, HR documents, and tribal company knowledge.

Learn more
03 · Docs

Product documentation chatbot

Let users ask natural-language questions about technical docs, API guides, and product manuals.

Learn more
04 · GTM

Sales & pre-sales assistant

Give prospects instant answers from offer documents, pricing rules, case studies and product information.

Learn more
05 · Enterprise

Document intelligence

Build secure AI assistants for legal, operational, compliance, and knowledge-heavy internal processes.

Learn more
06 · Ops

Internal ops copilots

Wire RAG into runbooks, dashboards, and SOPs so your operators stop hunting through wikis at 3 AM.

Learn more
Why RAG, not just AI chat?

A chatbot that knows your business, not a chatbot that's heard of it.

A general assistant answers from model training data. Ragable retrieves from the documents you indexed first and generates second, so answers stay tied to sources you control and can correct.

Dimension
Standard AI chatbot
Ragable RAG assistant
Source of truth
General model knowledge, plus whatever it remembers
Your indexed documents, retrieved at query time
Confidence
Can sound confident without sources
Source-grounded responses with citations
Knowledge control
Hard to update or contain domain
Knowledge bases you own, updated any time
Behavior
Generic, one prompt to rule them all
Configurable per use case, per audience
Deployment
Usually SaaS only
SaaS, private cloud, or on-premise
Hallucinations
Common, hard to attribute
Reduced by grounding answers in retrieved context
Inside the panel

The whole workflow, from indexing to embed, in one workspace.

Switch tabs to see what your team works in: knowledge bases, bot builder, live chat preview, the embed snippet, and usage analytics.

Folders
All bases
Product4
Support
Engineering
Legal
Archive

Product · 4 knowledge bases

356 documents · 2.26M tokens · last sync 18 min ago
Product docs · EU
184 documentsupdated 2h ago
1.2M tokens
indexed
Support FAQ
52 documentsupdated yesterday
318K tokens
indexed
Legal & policies
23 documentsupdated -
- tokens
processing
Engineering handbook
97 documentsupdated 3d ago
740K tokens
indexed
Pricing

Predictable plans for SaaS, custom infrastructure for enterprise.

Three SaaS plans cover most teams. Enterprise runs on a separate track: own deployment, own models, own terms.

Starter

For small teams and first production deploys.

$99/ month
  • Knowledge bases2
  • Monthly sessions1,000
  • Included tokens1.5M
  • Assistants1
  • Hosted SaaS · widget
  • Basic dashboard
  • Email support-
Start Starter

Scale

Production-grade for larger teams and applications.

$999/ month
  • Knowledge bases30
  • Monthly sessions50,000
  • Included tokens60M
  • Assistants15
  • Team seats10
  • Advanced analytics
  • Model provider config
Choose Scale

Enterprise

Private cloud, on-premise, or custom infrastructure.

Custom
  • DeploymentOn-prem · Private cloud
  • ModelsCloud · OSS · your own
  • IntegrationsCustom
  • Security review
  • SLATailored
  • Dedicated supportNamed team
  • ImplementationHands-on
Contact sales

Not sure which plan fits? Talk to us and we will size it with you.

All limits are reset monthly · Overage billed transparently
Enterprise · On-premise

Enterprise RAG infrastructure, adapted to your environment.

For organisations with strict security, data control, integration or compliance requirements, Ragable is adapted to private cloud, isolated infrastructure or on-premise deployment.

  • On-premise or private cloud deployment
  • Custom model providers: open-source, hosted or your own
  • Isolated infrastructure with security review
  • Custom data ingestion pipelines
  • Integration with internal systems (SSO, IdP, data lakes)
  • Access control, audit logs, retention policies
  • Named implementation team and dedicated support
  • Request enterprise consultation
Reference architecture
SourcesDocuments · APIs · Internal systems · Data lakes
IngestionChunk · clean · deduplicate · enrich
Vector / Searchpgvector · Weaviate · custom
RAG engineRetrieve · rerank · cite
ModelsOpenAI · Anthropic · OSS · self-hosted
SurfaceWidget · App · Panel · API
FAQ

Common questions, answered plainly.

A short version of our full FAQ. For pricing edge cases, enterprise specifics or security questionnaires, talk to us.

Ragable is a RAG platform for building AI assistants that answer questions from your own documents and knowledge bases, and cite the source each answer came from.

Not for the basics. You upload documents, configure an assistant in the panel, and embed it with a single JavaScript snippet. Enterprise work such as custom data pipelines, SSO or on-premise deployment usually needs a developer.

Yes. Ragable generates a chatbot widget you embed in any website or web app with one line of JavaScript. You can restrict allowed domains and theme the widget per surface.

Ragable indexes PDF, DOCX, Markdown, HTML, plain text and spreadsheets. Scanned PDFs go through OCR, so paper documents become searchable too.

Yes. Enterprise deployments run on your private cloud or on-premise infrastructure, with your data residency, a security review and hands-on implementation support.

No. Leading cloud models work out of the box, and enterprise deployments can use open-source, self-hosted or your own model providers.

Every SaaS plan includes monthly limits for sessions, tokens, knowledge bases and assistants. The pricing table lists the current values and overage is billed transparently.

Ragable retrieves relevant passages from your knowledge base before the model writes anything, and shows the sources behind each answer. That does not make hallucinations impossible, but it ties answers to retrieved context and lets a reader verify them.

Get started

Build your first AI knowledge assistant
with Ragable.

Self-serve from $99/month, or talk to our team about private and on-premise deployment.