Build an autonomous AI SDR
Give Jason a goal, knowledge, and guardrails — then supervise instead of operate.
Outcome: A self-optimizing outbound system - the AI SDR finds prospects, writes and sends outreach, handles replies, and books meetings, while your agent supervises through approval gates and performance data.
Availability: 3 of 8 steps coming soon — the rest is callable today.
The highest-altitude recipe: an agent configuring an agent. Instead of composing individual sends, your agent programs Jason — Reply’s AI SDR — and keeps a supervisory loop through approval gates and analytics. Today the knowledge/offer/playbook layer is callable; the autopilot loop is rolling out and labeled accordingly.
Steps
- Define the sales goal agent logic
The user states the objective; the agent translates it into an offer, a target market, and success metrics.
- Build the knowledge base
Create a knowledge base and upload product docs, links, reply handlers, and re-engagement cards — the facts Jason sells from. Uses AI SDR API (Jason) .
- Define offers and playbooks
Create the offer (what's being sold, to whom) and the playbook (tone, structure, channels, style). Uses AI SDR API (Jason) .
- Point it at prospects Coming soon
Use intent signals and Live Data search to define who the autopilot pursues. Uses Prospect Search API .
- Enable autopilot with approval gates Coming soon
Create an AI SDR sequence, connect the knowledge base and playbook, set approval mode, and enable autopilot. Uses AI SDR API (Jason) .
- Supervise the queue Coming soon
Review pending approvals — approve, regenerate, or reject drafts; submit feedback that tunes future generations. Uses AI SDR API (Jason) .
- Watch the conversations
Replies flow into the unified inbox with AI categorization; escalate to a human when intent is high. Uses Conversations & Inbox API .
- Optimize on outcomes
Read performance reports and the meetings ledger; refine the offer, playbook, and targeting based on what converts. Uses Analytics API .