Smarter Data Entry for Harvest Teams
Turn Data Entry into a background job. Arahi AI agents use Harvest to execute on your behalf, 24/7.
47 PDFs processed today. Latest entry:
Meeting notes
- • Vendor: Riverline Co. · Term: 12 months from Apr 1.
- • Total contract value: $42,000 net 30.
- • Signed by: Theo Park (CEO, Riverline) + Daniel R. (Arahi).
How does Harvest work for data entry automation?
Harvest works for data entry automation by powering an Arahi AI agent that runs the workflow end-to-end inside your existing tools — no code, no custom build. The agent connects to Harvest alongside the other apps your team already uses, watches for the triggers that matter for data entry, and takes the next step on its own while keeping a complete audit trail for review. AI extracts, validates, and enters data from documents, emails, and forms automatically. Teams typically see high across mixed document formats once the agent is in production. 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.
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.
- 1Read the meeting transcript end-to-end
- 2Extract decisions, commitments, and next steps
- 3Update the deal record and advance the stage if criteria met
- 4Notify the right teammate with the relevant context
Get started in three steps
Connect Harvest
Link Harvest to Arahi AI in one click. Your tasks, projects, and documents sync automatically.
Set Up Workspace Automation
Define triggers in Harvest — new tasks, status changes, due dates — and the AI actions that follow.
Work Smarter, Not Harder
Your AI agent keeps Harvest organized while you focus on execution. Track productivity gains on your dashboard.
Vendor: Riverline Co. · Term: 12 months from Apr 1.
Action items extracted; assignees notified in Slack.
Three deals moved to next stage; risks flagged for the AE.
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.
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.
- Agent2:47 PM
Updated Sheets · Vendor agreements with the meeting outcome.
- Agent2:46 PM
Advanced deal stage; the criteria for Proposal were met.
Reason: Budget confirmed and decision-maker identified per stage definition.
- Agent2:45 PM
Wrote meeting notes for PDF · Vendor agreement · Riverline.pdf.
- Agent2:44 PM
Read the transcript and extracted action items.
- Agent2:30 PM
Triggered by call end event in Granola.
Frequently asked questions
Manual data entry in Harvest requires constant tab-switching, copy-pasting, and follow-up tracking. Arahi AI eliminates this by handling data entry tasks in real-time as Harvest events occur — running 24/7 with consistent accuracy and zero fatigue.
Yes. You can run data entry workflows in test mode using sample Harvest data before activating on live records. This lets you verify every data entry rule works correctly with your Harvest setup before processing real data.
Yes. You define exactly which Harvest events start data entry workflows — new records, status changes, messages, or custom triggers. Each trigger can have conditions so data entry actions only fire when your specific criteria are met in Harvest.
Yes. The data entry agent connected to Harvest simultaneously interacts with 1,500+ other apps — CRMs, databases, email platforms, and more. A single data entry workflow can pull data from Harvest, process it, and push results to multiple destinations.
The agent reads PDFs, scanned images, emails, spreadsheets, and structured forms — extracting data fields and writing them to your systems. Even handwritten forms common in harvest (intake, work orders, inspection reports) are processed accurately.
Validated extraction accuracy typically exceeds 98% on standardized documents — significantly better than the 4-5% error rates common with manual data entry in harvest environments. Edge cases below the confidence threshold are flagged for human review instead of guessed.
Teams automating data entry through Harvest typically save 10-20 hours per week on manual processing. The ROI dashboard tracks time saved, tasks completed, and error reduction so you can quantify exactly what Harvest-powered data entry automation delivers.
The Harvest integration maintains a persistent real-time connection for data entry automation with automatic retry logic and continuous monitoring. If Harvest experiences downtime, queued data entry tasks process automatically once connectivity resumes.
Arahi AI connects natively with Harvest to handle the full data entry workflow. The AI agent monitors Harvest events, processes data entry tasks automatically, and writes results back to Harvest — no copy-pasting or tab-switching required.
Yes. You can create parallel data entry workflows that respond to different Harvest events or conditions. For example, one data entry flow for new Harvest records and another for updated ones — each with independent rules and actions.
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