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Askli
No-code custom chatbot trained on your data, deployed across web, WhatsApp, Slack and Telegram
0Visit Askli
https://www.chaindesk.ai
About Askli
Askli — the product formerly and still domain-named Chaindesk — is a no-code platform for training a custom GPT-4-class chatbot on your own company data and deploying it across every channel your customers already use. The pipeline is four steps: import data from files, Notion, Google Drive, a Zendesk help centre or any public URL; configure the agent's persona, goals and branding; deploy to a website widget or into existing tools; then monitor conversations and take over manually when the AI should not be the one answering. Built-in safeguards constrain responses to the knowledge base, which is the mechanism that stops a support bot wandering off-topic. Beyond the widget, the platform is closer to a small support suite than a single bot: a shared inbox consolidates conversations across channels with team assignment, an AI-assisted email inbox handles support mail, conversational forms collect user information in dialogue rather than as a form, function calling lets agents hit your own API endpoints, and lead-generation capture runs inside the conversation. Datasources auto-sync so the bot retrains when source content changes. Omnichannel coverage spans embeddable widgets, WhatsApp, Slack, Telegram, Messenger, Shopify, Crisp, Zendesk and Zapier. The company is French and stresses that data is encrypted in transit and at rest. The vendor claims resolution of around 80% of support queries.
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Key Features
Askli Pros & Cons
✅ Pros
- +Team seats are generous — 10 on the $49 tier where rivals charge per seat
- +Function calling makes the bot actionable rather than purely informational
- +EU-based with encryption at rest and in transit, which simplifies GDPR review
⚠️ Cons
- −Free-tier agents are deleted after 14 days of inactivity
- −The Chaindesk-to-Askli rebrand is incomplete, so branding is inconsistent across the site
- −Message credits are quoted against gpt-4o-mini; better models consume them faster
Tags
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