ChattyDocs is live · pricing from $9/mo · last verified 24 Oct 2026 · viability monitor
ChattyDocs
ChattyDocs is a document Q&A assistant: upload PDFs or web links, ask questions in plain language, get answers with cited sources.
ChattyDocs wins on citation transparency for the money: page-level source attribution on uploaded files, link-level on websites, at $9/month for 20 datasets and 1,000 monthly queries. The catch is volume in both directions — 7 MB of upload text per month on Casual and 35 MB on Scale are small allowances, and a scanned or image-heavy PDF without a clean text layer is outside what this pipeline handles. If your corpus is text-native PDFs and you want cheap, verifiable answers, it fits. If you need to push hundreds of megabytes or work with tables and screenshots, budget for the $399/month Enterprise tier or look at document Q&A tools built around multimodal ingestion.
Verdict generatedVerified 6d ago · liveness 64/100 · cite: rightaichoice.com/tools/chattydocs
- Solo researchers with text-native PDF collections
- Legal and compliance reviewers who need cited answers
- Students working from lecture notes and textbooks
- Small support teams publishing queryable documentation
- Teams whose archives are scanned PDFs or image-heavy documents
- Anyone needing to ingest hundreds of megabytes of text per month
- Teams expecting simultaneous multi-user collaboration inside a dataset
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Skip ChattyDocs if you need to ingest hundreds of megabytes of text a month, work mainly from scanned or image-heavy PDFs, or need several people editing the same dataset at once — the tiered upload credit and text-only pipeline will get in your way.
Upload text is metered per month, so a batch of large PDFs can burn through the 7 MB Casual or 35 MB Scale allowance before you finish your first project.
At $9/month Casual, ChattyDocs undercuts most subscription document-Q&A tools, but the 7 MB monthly upload allowance is small enough that many buyers will need $49/month Scale for 35 MB, 100 datasets and API access. The $399/month Enterprise tier is priced for organizations that need 200 MB of upload, 30,000 queries and priority support — above that, a self-hosted custom arrangement is the only published path.
In short
ChattyDocs — ChattyDocs is a document Q&A assistant: upload PDFs or web links, ask questions in plain language, get answers with cited sources. Best for Solo researchers with text-native PDF collections, Legal and compliance reviewers who need cited answers, Students working from lecture notes and textbooks. Plans from $9/mo.
What is ChattyDocs?
ChattyDocs — ChattyDocs is a document Q&A assistant: upload PDFs or web links, ask questions in plain language, get answers with cited sources. Best for Solo researchers with text-native PDF collections, Legal and compliance reviewers who need cited answers, Students working from lecture notes and textbooks. Plans from $9/mo.
ChattyDocs turns your own documents into a question-answerable knowledge base. You upload PDFs or any kind of text file from your device using the built-in upload manager, or paste a website link and let the service fetch and parse the page as a data source. Indexing happens in the background, so you are not stuck waiting for a progress bar. Once a dataset is ready you set its properties — choosing the chat model, allocating how much context goes to history versus output, adjusting temperature to make answers more creative or more deterministic, and writing a system prompt that gives the assistant a name, a tone and a preferred language. Answers come back with the sources attached: for a multi-page upload you see the document name and the page number, and for website sources you get a link. Beyond chat, you can create a public dataset and share it by link, run multiple persisted chat sessions per dataset so you can pick up where you left off, attach standing chat context that is folded into every query, export all questions and answers with one click, and track how much of your monthly upload credit each file or website will consume. The interface is available on desktop, on mobile, and through Telegram bots, and there is an embedded web chat you can drop into a page. Plans are priced per month and cancellable anytime: Casual at $9/month, Scale at $49/month, Enterprise at $399/month, plus a free trial of 20 queries and 900 KB of upload text with no credit card required. API access starts at Scale; a self-hosted Docker deployment of the database, vector store and web application is a custom plan. It is built for text-centric document work where verifiability matters — literature reviews, contract and case-file review, textbook study — rather than for image-heavy or scanned material.
Key features
- Upload PDFs and any text file from your device
- Upload a website link and have data downloaded and parsed automatically
- Background indexing so uploads do not block you
- Answers with source attribution: document name and page number, or website link
- Choose the chat model per dataset
- Control how context, history and output sizes are allocated
- Temperature control for creative versus deterministic answers
- System prompts to set the AI's name, personality and language
- Add or delete documents from a dataset at any time
- Multiple persisted chat sessions per dataset
- Standing chat context included in every query
- Export all questions and answers with one click
- Public dataset sharing via link
- Telegram bot integration (1 to 30 bots depending on plan)
- API access on Scale and Enterprise
Our long-form take written Jul 29, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Limitations
- Upload credit is the real ceiling: 7 MB of text per month on Casual, 35 MB on Scale and 200 MB on Enterprise, and queries are capped at 1,000, 5,000 and 30,000 per month respectively.
- The free trial is 20 queries and 900 KB of upload text.
- API access does not start until the $49/month Scale tier.
- Per-dataset document counts are tiered too (30 documents per dataset on Casual, unlimited on Scale and Enterprise), and Telegram bots are limited to 1, 10 or 30.
- Self-hosting is a custom Docker arrangement rather than a listed plan.
- The pipeline is aimed at text documents, so scanned or image-heavy files without a usable text layer are a poor fit, and there is no indication of real-time collaboration inside a dataset.
as of 2026-10-04
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Is ChattyDocs still active?
ChattyDocs is live · pricing from $9/mo · last verified 24 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is ChattyDocs? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about ChattyDocs?
What people actually say about ChattyDocs — is it worth it?
Our community sentiment research written Jul 5, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about ChattyDocs— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 24 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified ChattyDocs 11 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed SSL certificate
- — changed description, our verdict, features, hidden costs, who it suits, limitations, switching in, switching out, who should skip it, pricing tiers, pricing fit, setup time, summary, use cases
- — changed limitations
- — changed pricing tiers, hidden costs, who should skip it, setup time, limitations, pricing fit, switching in, switching out
- — changed domain expiry
- — changed SSL certificate
Showing the 6 most recent of 11 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does ChattyDocs cost in 2026?
ChattyDocs: Plans from $9/mo. Pricing last verified 24 Oct 2026.
Plans compared
Every published ChattyDocs tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Casual | $9/mo | monthly | A solo researcher, student or independent professional querying a small set of text PDFs who wants cited answers at the lowest monthly cost.Adds: Starting paid tier at $9/month: 20 datasets, 30 documents per dataset, 1 Telegram bot, 7 MB of upload text and 1,000 queries per month. |
| Scale | $49/mo | monthly | A professional or small team whose corpus has outgrown 30 documents per dataset or 1,000 monthly queries and who needs programmatic access.Adds: Adds API access versus Casual, and raises the ceilings to 100 datasets, unlimited documents per dataset, 10 Telegram bots, 35 MB of upload text and 5,000 queries per month. |
| Enterprise | $399/mo | monthly | An organization running a large internal knowledge base or a high-traffic public dataset that needs priority support.Adds: Removes the dataset and per-dataset document limits and raises quotas to 30 Telegram bots, 200 MB of upload text and 30,000 queries per month, with priority support on top of Scale's API access. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where ChattyDocs's pricing actually pencils out — and where peers do it cheaper.
At $9/month Casual, ChattyDocs undercuts most subscription document-Q&A tools, but the 7 MB monthly upload allowance is small enough that many buyers will need $49/month Scale for 35 MB, 100 datasets and API access. The $399/month Enterprise tier is priced for organizations that need 200 MB of upload, 30,000 queries and priority support — above that, a self-hosted custom arrangement is the only published path.
Has ChattyDocs' pricing changed?
No plan price for ChattyDocs has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick ChattyDocs?
Pick ChattyDocs if you are Solo researchers with text-native PDF collections, Legal and compliance reviewers who need cited answers, Students working from lecture notes and textbooks, Small support teams publishing queryable documentation.
Look elsewhere if you are Teams whose archives are scanned PDFs or image-heavy documents, Anyone needing to ingest hundreds of megabytes of text per month, Teams expecting simultaneous multi-user collaboration inside a dataset, High-volume programmatic workloads that would need API access on the $9/month Casual tier.
Skip it if Skip ChattyDocs if you need to ingest hundreds of megabytes of text a month, work mainly from scanned or image-heavy PDFs, or need several people editing the same dataset at once — the tiered upload credit and text-only pipeline will get in your way.
GeneratedReal-world workflow fit
Concrete scenarios for the personas ChattyDocs actually fits — and what changes day-one when you adopt it.
Uploads a folder of text-based PDF papers into one dataset, sets a low temperature for factual extraction, then asks questions across the collection and reads the document name and page number behind each answer.
Outcome: A cited answer trail she can export in one click and paste into a literature review, without re-reading every paper.
Creates a dataset per matter, uploads contracts and filings, writes a system prompt that keeps answers terse and clause-focused, and shares a public dataset link with the attorney handling the case.
Outcome: The attorney queries the matter's documents directly and sees which page each answer came from, while the paralegal keeps a separate chat session for her own follow-ups.
Points a dataset at the product documentation website link, assigns a Telegram bot, and shares the dataset so customers can ask questions in chat.
Outcome: Customers get answers that link back to the exact documentation page, and the team can export the question log to see what the docs are failing to explain.
Use cases
- Researchers uploading and querying PDF papers for a literature review and getting page-level citations
- Legal professionals asking targeted questions across case files and contracts with the source document returned
- Students querying textbooks or lecture notes and exporting the answers as study notes
- Content creators curating several websites into one dataset and asking questions across the links
- Support teams publishing product documentation as a public dataset link clients can query
- Small teams building an internal searchable knowledge base with the self-hosted Docker option
Setup time & first value
How long it actually takes to get something useful out of ChattyDocs — broken out by persona, not the marketing-page minute.
A single small PDF dataset is chat-ready in a few minutes — upload, pick a model, set temperature and a system prompt, and background indexing finishes shortly after. Pointing a dataset at a website link is similarly quick. Budget longer for a first serious corpus: with a 7 MB monthly Casual allowance or 35 MB on Scale, you will want to check the usage tracker before bulk-uploading.
Switching to or from ChattyDocs
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From general-purpose chatbots: upload your source PDFs or paste the website link, then add a system prompt that constrains answers to the supplied documents.
- →From a manual PDF reader workflow: create one dataset per project, upload the files, and use persisted sessions so your question history survives between sittings.
- →From a shared drive of documentation: publish the dataset as a public link or attach a Telegram bot so readers query the docs instead of downloading them.
- ↗To a multimodal document tool: move over if your corpus includes scanned pages, tables or screenshots that need OCR or image understanding.
- ↗To a larger-volume text platform: switch if 200 MB of upload text per month on Enterprise is still not enough for your archive.
- ↗To a collaborative research workspace: switch if several people need to annotate and chat over the same dataset simultaneously rather than through a shared link.
Integrations
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “ChattyDocs”, and we withheld 6: 6 could not be judged, because “ChattyDocs” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about ChattyDocs.
Official links
What are the best ChattyDocs alternatives?
The closest alternatives to ChattyDocs we list are Humata AI, AskYourPdf and Myreader AI. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Humata AI | Freemium | Pricing not published | — |
| AskYourPdf | Freemium | Pricing not published | — |
| Myreader AI | Freemium | Pricing not published | — |
Alternatives to ChattyDocs
View all
Humata AI
Humata AI is a PDF AI that answers questions across your documents with citations linking back to the exact source passage
AskYourPdf
Chat with PDFs in plain language, auto-fill any PDF form from your own documents, and embed a website AI agent trained on your content.
Myreader AI
Chat with your PDFs, ebooks and YouTube links — get cited answers that jump to the exact page.
Tools that pair well with ChattyDocs
Common stack mates teams adopt alongside ChattyDocs, with the specific reason each pairing earns its keep.
Humata AI
Humata AI is a PDF AI that answers questions across your documents with citations linking back to the exact source passage
AskYourPdf
Chat with PDFs in plain language, auto-fill any PDF form from your own documents, and embed a website AI agent trained on your content.
Myreader AI
Chat with your PDFs, ebooks and YouTube links — get cited answers that jump to the exact page.
ChattyDocs vs its closest rival
ChattyDocs's closest head-to-head is with Screenplayiq — If you need data-driven script analysis with box office predictions, choose ScreenplayIQ — it's purpose-built for screenwriters and industry pros. For general document analysis over large collections of PDFs and texts, ChattyDocs offers flexible AI interactions with source attribution. Both serve distinct needs with no overlap; pick based on your content type. Verdict generated
Head-to-head comparisons
Chattydocs vs Screenplayiq
If you need data-driven script analysis with box office predictions, choose ScreenplayIQ — it's purpose-built for screenwriters and industry pros. For general document analysis over large collections of PDFs and texts, ChattyDocs offers flexible AI interactions with source attribution. Both serve distinct needs with no overlap; pick based on your content type.
GeneratedChattydocs vs Versatile
If you're a steel erector needing crane-specific intelligence without workflow changes, Versatile is unmatched—but it's expensive and narrow. For anyone analyzing large document collections with customizable AI, ChattyDocs offers flexible pricing (starting at $20/mo) and features like source linking, making it a clear win for researchers and legal teams.
GeneratedChattydocs vs Geologicai
GeologicAI is a purpose-built, high-cost enterprise platform for critical minerals mining, offering end-to-end sensor scanning and AI modeling. ChattyDocs is a versatile, affordable document-analysis AI for knowledge workers. They serve completely different audiences; choose GeologicAI if you're in large-scale mining and need sub-48-hour core analysis, or ChattyDocs for text-heavy research and document QA.
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