AI Agent for Chat Support — Built for BigML
Automate Chat Support for teams using BigML. DeskFerry agents handle the workflow end-to-end — no code, set up in minutes.
84 chats handled overnight. Sample resolution:
Customer
“Hey — my Slack agent stopped firing after I rotated the workspace token yesterday. Anything I need to do on my end?”
Agent draft · in your tone
Hi Lara — totally normal, the new token needs a quick re-auth. I've sent a one-click reconnect link to your DeskFerry inbox; once you tap it the agent will pick up where it left off (no re-training needed).
How does BigML work for Chat Support automation?
BigML works for Chat Support automation by powering a DeskFerry agent that runs the workflow end-to-end inside your existing tools — no code, no custom build.
- 01
Trigger fires
The agent connects to BigML alongside the other apps your team already uses, watches for the triggers that matter for Chat Support, and takes the next step on its own while keeping a complete audit trail for review.
- 02
Answer live @Intercom chats using @BigML in our brand voice
AI handles common questions immediately, reducing wait times to zero for routine inquiries.
- 03
Escalate the rest with full context to @Zendesk
Teams typically see instant around the clock once the agent is in production.
- 04
You approve
You stay in control: every action is logged, confidence thresholds are configurable, and anything ambiguous is queued for a human instead of being silently auto-completed.
How you tell it what to do
Built in plain English.
You write the rule the way you'd describe it to a teammate. The agent reads the rule, breaks it into the actions it'll take, and confirms the apps it'll touch — before it does anything.
- 1Answer live @Intercom chats using @BigML in our brand voice
- 2Escalate the rest with full context to @Zendesk
How it connects
Connect BigML. The agent does the rest.
Claude and ChatGPT are already running on our side. You connect BigML with one click, and chat support runs inside it.
Claude and ChatGPT run on our keys. Nothing for you to configure.
- BigMLConnect
- IntercomConnect
- ZendeskConnect
Runs on your data, in your apps.
Nothing to deploy. Nothing to maintain.
Actions
What BigML + DeskFerry can do
Real BigML actions your AI agent can perform automatically — no manual work required.
Create issues from alerts
Automatically open issues in BigML when monitoring systems detect errors, outages, or performance regressions.
Manage pull requests
Post review reminders, enforce labeling conventions, and auto-merge approved pull requests in BigML.
Trigger CI/CD pipelines
Kick off build and deployment pipelines in BigML when code is pushed or a pull request is merged.
Track release milestones
Update milestone progress in BigML as issues are closed and pull requests are merged toward a release.
Sync project boards
Keep issue status and priority in BigML aligned with your project management tool in real-time.
Generate changelogs
Compile merged pull requests and closed issues from BigML into formatted release notes automatically.
Assign reviewers automatically
Route new pull requests in BigML to the appropriate code reviewers based on file ownership and team rules.
Monitor repository activity
Watch for commits, branch creations, and tag events in BigML and notify the team of significant changes.
Hi Lara — totally normal, the new token needs a quick re-auth. I've sent a one-click reconnect link to your DeskFerry inbox; once you tap it the agent will pick up where it left off (no re-training needed).
Customer reports a duplicate charge; refund queued, awaiting confirmation.
Customer asking what's included on the Growth plan vs. Pro.
Human in the loop
Approve before it sends.
Every draft lands in a review queue. You approve, edit, or reject — the agent never acts on its own unless you explicitly turn that on for a workflow you trust.
Governance
Every action, with the reasoning attached.
Each step the agent takes is logged with what it did, why it did it, and which app it touched. Audit-ready, so security and compliance can sign off without backfilling.
- Lara Knight9:14 AM
Customer marked the resolution as helpful.
- Agent9:12 AM
Sent reply on ticket #9281.
Reason: Confidence above auto-send threshold; voice match passed; SLA at-risk.
- Agent9:11 AM
Drafted reply in your team's voice.
- Agent9:10 AM
Pulled customer plan, prior tickets, and account context.
- Agent9:09 AM
Triaged #9281 as the matching topic.
How it works
Get started in three steps
Step 01
Connect BigML
Authorize BigML and DeskFerry hooks into your issues, repos, and deployment pipelines.
Step 02
Configure Dev Workflows
Define triggers for BigML events — new issues, PR merges, build failures — and the AI actions to take.
Step 03
Ship Faster with Less Toil
AI automates the tedious parts of your BigML workflow. Track issues triaged, alerts handled, and developer time saved.
Start automating Chat Support for BigML
7-day free trial. Works with the tools you already use.
FAQ
Frequently asked questions
What specific Chat Support tasks can the BigML integration automate?
The BigML integration automates end-to-end Chat Support — including data capture from BigML, validation, routing, follow-up actions, and status updates. Every Chat Support step that touches BigML can be handled by the AI agent.
Can I test Chat Support automation with BigML before going live?
Yes. You can run Chat Support workflows in test mode using sample BigML data before activating on live records. This lets you verify every Chat Support rule works correctly with your BigML setup before processing real data.
Can the BigML Chat Support agent also work with other tools in my stack?
Yes. The Chat Support agent connected to BigML simultaneously interacts with 1,500+ other apps — CRMs, databases, email platforms, and more. A single Chat Support workflow can pull data from BigML, process it, and push results to multiple destinations.
How does DeskFerry automate Chat Support directly inside BigML?
DeskFerry connects natively with BigML to handle the full Chat Support workflow. The AI agent monitors BigML events, processes Chat Support tasks automatically, and writes results back to BigML — no copy-pasting or tab-switching required.
How does AI-powered Chat Support via BigML compare to manual processing?
Manual Chat Support in BigML requires constant tab-switching, copy-pasting, and follow-up tracking. DeskFerry eliminates this by handling Chat Support tasks in real-time as BigML events occur — running 24/7 with consistent accuracy and zero fatigue.
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