Chat Data

· #428 most-used

Build AI chatbots on your data — capture leads, answer live

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Chat Data is a no-code AI chatbot platform that lets you train custom bots on your documentation, website content, and files — then embed them anywhere to handle support, capture leads, and guide visitors 24/7. Connect it to Actionist and your agents can read conversation histories, trigger retraining when your knowledge base changes, route live-chat escalations to the right human in seconds, and pull lead and confidence-score data into CRM or reporting pipelines without a single manual export.

Try Chat Data with Actionist Visit Chat Data

Average time saved

10 hours

per person · per month

≈ 1 workdays back

Eliminates manual work. Eliminates manual chat log review, copy-paste lead entry into CRM, and the weekly ritual of checking which chatbot topics are returning low-confidence scores.

Schedule

What your Chat Data agent runs on autopilot

A week of scheduled jobs your Actionist agent will execute on your behalf.

28Scheduled jobs

7Agents at work

24/7Always on

Agents

Wed–Fri

Wed

Thu

Fri

10a

11a

12p

Multi-app workflows

Chat Data × every other app you use

End-to-end automations that span multiple apps — each one a real business outcome.

6Workflows

9Apps spanned

~30 hrsSaved / week

6Personas served

For customer success

Featured4 apps

Support email → resolved in 90 seconds

When a customer support email lands in Gmail, your agent reads the full thread, queries your Chat Data knowledge base for the exact answer, fires back a confident draft reply, notifies the CS team in Slack so they can approve in one click, and blocks a review slot on Google Calendar — all before a human has even opened their inbox. Customers get an accurate, brand-consistent answer faster than a coffee run; your team stops spending 60 minutes a day copy-pasting from documentation.

~10 hrs

Time saved for your team — every week, on autopilot

The flow

Trigger·When a new customer email arrives in the Gmail support inbox

Trigger

Step 1

Gmail

New email in support inbox

read

Step 2

Chat Data

Query knowledge base for answer

write

Step 3

Chat Data

Send reply message via chatbot channel

write

Step 4

Slack

Post draft reply for CS team approval

write

Step 5

Google Calendar

Block 15-min review slot for the assigned rep

Result

Send reply message via chatbot channelPost draft reply for CS team approvalBlock 15-min review slot for the assigned rep

The win

Saved per run

~1 hrs

Runs / week

~10×

Zero unanswered support emails

Driven byCustomer Support Agent

ROI

Savings

What your team gets back — two angles: what you stop doing manually, and what that's worth.

Without Actionist

What you do manually today

With Actionist

What your agent runs for you

Sales
18 min / week
Manual lead log review
Reps scan chat transcripts each morning to identify hot leads, copy names and emails into the CRM, and guess intent from conversation snippets.
Sales Agent
0 min
Agent logs and scores every lead automatically
When a lead form fires, the agent extracts contact data, scores intent against your ICP criteria, and writes a deal into the CRM before the rep's morning standup.
Marketing
13 min / week
Chatbot FAQ gap audit
Marketers manually read low-confidence chat logs each week to identify content gaps and draft new FAQ entries for the knowledge base.
Marketing Agent
0 min
Agent logs gaps and triggers retraining
When a low-confidence event fires, the agent records the question in a gap-log sheet and queues a retraining run once three unique gaps are logged.
Customer Support
18 min / week
Escalation routing by hand
Support leads manually assign escalated chats to the right rep, copy the transcript into the ticket, and set priority — taking 3–5 minutes per escalation.
Customer Support Agent
0 min
Agent routes escalations in seconds
When a live-chat escalation fires, the agent checks who is on-call, creates the ticket with the full transcript, and DMs the assigned rep in Slack — all in under 30 seconds.
Human Resources
7 min / week
Onboarding bot content review
HR manually audits the onboarding chatbot's conversation logs quarterly to check if new-hire questions are being answered correctly and flags outdated content.
Human Resources Agent
0 min
Agent flags stale onboarding content weekly
Every Friday the agent queries the onboarding bot's low-confidence responses and posts a digest of unanswered new-hire questions to the HR Slack channel for same-day action.
Finance
13 min / week
Chatbot ROI export
Finance manually pulls conversation volume, lead counts, and chatbot statistics from the Chat Data dashboard into a spreadsheet to calculate monthly ROI.
Finance Agent
0 min
Agent compiles the ROI report automatically
Each month the agent fetches chatbot statistics and lead data from Chat Data, maps them to revenue in HubSpot, and files the summary in the finance Notion workspace.
Operations
25 min / week
Knowledge base sync to chatbot
Ops teams manually upload updated product docs, release notes, or policy changes to Chat Data and trigger retraining — a 20–30 minute cycle per update.
Operations Agent
0 min
Agent retrains on every doc change
When a new row lands in the FAQ sheet or a doc is updated, the agent uploads the file and triggers a Chat Data retrain within minutes, then logs the event in Notion.
Legal
6 min / week
Webhook audit log
Legal manually checks active chatbot integrations quarterly to confirm registered webhooks comply with data-residency policies and removes stale endpoints.
Legal Agent
0 min
Agent maintains a live webhook audit trail
When any webhook is registered, the agent appends the endpoint, chatbot scope, and timestamp to the compliance spreadsheet — giving legal a real-time integration inventory.

+ 100s of other Chat Data automations

Average monthly

10 hrs / person / month

Average monthly

10 hrs / person / month

Calculator

Calculate what your team saves

Team size

10 person

Hourly rate

$20 / hr

Hours saved / week

Hours saved / year

1,250

Annual ROI

$25,000

Based on Chat Data's typical team usage — the visible tasks plus a few other automations the agent runs: ~2.5 hrs / person / week of admin work automated.

Connect

How to plug Chat Data into Actionist

Pick the connection method that suits your environment.

The fastest path. Install Chat Data's MCP server in one click; the agent reaches your chatbots, conversations, and lead data through a permissioned handshake — no API keys to rotate, no token scopes to misconfigure.

Open the Apps tab

Find Chat Data in the Apps library and click Connect. MCP is selected by default.

Authorise in Chat Data

You'll be redirected to chat-data.com to approve the connection. Select which chatbot workspaces Actionist may access, then confirm. Chat Data issues a scoped session token automatically.

Test the connection

Actionist runs a read-only call to verify the handshake. You're ready.

Actions

20 action your agent can call

Read and write operations available to your Actionist agent.

Triggers

7 event your agent can react to

Events your agent watches for, and the actions it kicks off in response.

Skills

Skills that pair with Chat Data

Reusable agent skills that work well alongside this app.

No paired skills curated yet. Add this app to your agent to discover what fits.

MCP servers

MCP servers that work with Chat Data

Connect Actionist to MCP servers built for or around this app.

No MCP servers indexed for this app yet.

FAQs

Questions about Chat Data + Actionist

What credentials does Actionist need to connect to Chat Data?

Actionist connects via the MCP method (recommended) or an API token. For MCP, you authorise Actionist through a Chat Data permission screen that scopes access to the workspaces you select — no token to store or rotate. For the API token method, generate a key in Chat Data's Dashboard → Settings → API Keys, paste it into Actionist, and the agent will use it for all subsequent calls. Revoke the key from Chat Data at any time to instantly disconnect.

Which Chat Data objects can the agent read and write?

The agent covers the full Chat Data API surface: chatbot configuration (create, update settings, update base prompt, delete), training (upload files, trigger retraining, check training status), conversations (list, fetch single, append messages, toggle live-chat mode), leads (read submitted forms), knowledge base queries, confidence scores, webhook management, and analytics. In short: if you can do it in the Chat Data dashboard, the agent can do it programmatically.

How do I avoid a trigger loop when my agent updates a chatbot?

Two safeguards: first, Chat Data triggers like 'Chatbot retrain completed' fire only on real retraining events initiated from outside Actionist, not on every API write — so a simple Update chatbot settings call does not re-fire the trigger. Second, build a condition step in your workflow that checks a session flag or a timestamp field before triggering retraining, so a bot that was trained fewer than 60 minutes ago is skipped. Never build an agent that chains 'Retrain chatbot' directly to 'Chatbot retrain completed' without such a guard.

Can the agent handle multiple chatbots in the same account?

Yes. Get all chatbots returns every bot in your Chat Data account, and every write action (update settings, retrain, update base prompt) accepts a chatbot ID parameter — so the agent can manage a fleet of bots, apply bulk changes conditionally, or route triggers to the correct bot by ID. Use Get all chatbots at the start of a workflow to build a dynamic selection list rather than hard-coding bot IDs.

How does the agent handle a Chat Data API rate limit?

Chat Data's API enforces per-account rate limits. Actionist applies automatic exponential back-off on HTTP 429 responses, retrying up to three times before surfacing an error to your workflow. For high-volume use cases — such as syncing leads from hundreds of conversations — use Actionist's built-in scheduling to spread calls across time rather than firing a burst all at once. The Get chatbot statistics and Get all chatbots endpoints are lightweight and well-suited to frequent polling.

What happens to in-progress live chats when the agent calls Toggle live chat state?

Toggle live chat state flips the chatbot's live-agent mode flag in Chat Data. If a visitor is mid-conversation when you switch to live mode, the chatbot hands control to a human agent but the conversation thread remains open and all prior messages are visible. Switching back to bot mode while a human agent is actively typing does not forcibly end their session — the next visitor message routes back to the bot. Test this in a staging chatbot before deploying to production.

Can I schedule the agent to retrain my chatbot on a recurring basis?

Absolutely. Pair the Actionist scheduler with the Retrain chatbot and Upload training file actions to run a weekly or daily refresh cycle. A typical pattern: the agent fetches updated docs from a Google Drive folder or Notion page on a cron, uploads the changed files to Chat Data, triggers retraining, and writes the training status to a log sheet. Use Get chatbot training status to poll for completion before firing any downstream notifications.

How do I disconnect Chat Data from Actionist?

Go to Actionist → Apps → Chat Data → Manage connection and click Disconnect. For MCP connections, this revokes Actionist's session token in Chat Data immediately — no further API calls will succeed. For API token connections, also go to Chat Data Dashboard → Settings → API Keys and delete the token there to ensure the credential is fully invalidated. Neither disconnect method affects your Chat Data chatbots, conversations, or data — it only removes Actionist's access.