A real AI SDR must ship seven non-negotiable features: per-prospect research, individualized copy generation, multi-channel orchestration, deliverability infrastructure, reply classification, CRM integration, and human-in-the-loop controls. Anything missing one of these is a sequencer with marketing copy. Buy on capability, not on AI-sounding feature names.
Why does feature completeness matter so much for AI SDRs?
Because the failure mode of an incomplete AI SDR is silent. You won't know you bought a sequencer-with-a-button until month two, when reply rates have flatlined and your deliverability is collapsing. Feature gaps don't show up in the demo — they show up in week eight. The seven features below are the ones whose absence destroys deployments.
What does "per-prospect research" actually mean as a feature?
Per-prospect research means the system reads something about every individual before writing to them. Real implementations pull from: the prospect's company website (product pages, about page, blog), recent news (funding, hires, launches), LinkedIn activity (posts, comments, role changes), tech stack signals, and hiring pages. The output is structured insight that feeds the copy generator — not raw text dumped into a prompt.
Test it in the demo: ask the vendor to research five prospects of your choosing and show you the structured output before any email is written. If they can't, the research layer doesn't exist.
How do I verify the copy generation is actually individualized?
Ask for ten generated emails to ten different prospects in the same ICP. Read the opening lines. If you can swap them between prospects without anyone noticing, the copy isn't individualized — it's templated with a research-flavored garnish. Real individualization produces opening lines that would feel weird sent to anyone else.
What does multi-channel orchestration require beyond "email + LinkedIn"?
- Shared state. A LinkedIn reply pauses the email cadence automatically.
- Channel-appropriate copy. The LinkedIn message isn't a copy-paste of the email.
- Sequencing logic. Email first, LinkedIn connection second, follow-up email third — configurable per ICP.
- Rate limits per channel. LinkedIn safe limits are far below email volume.
- Per-prospect channel preference. If the prospect responds on email, future touches stay there.
What deliverability infrastructure should be included by default?
- Inbox rotation across multiple domains and mailboxes.
- Automated warm-up that runs continuously, not just before launch.
- SPF/DKIM/DMARC validation with active monitoring.
- Per-inbox sending caps that adjust based on reputation signals.
- Bounce and complaint handling that pauses domains before they're blacklisted.
What does good reply classification look like?
Good reply classification distinguishes at minimum: positive (want to talk), negative (not now / no), referral (talk to my colleague), out-of-office, unsubscribe request, and ambiguous. Each category routes differently: positive to AE, referral to a new sequence with the right person, unsubscribe to suppression list, ambiguous to human review. Vendors that only output "positive/negative" force human review on everything, which defeats the point.
Why is CRM integration a must-have, not a nice-to-have?
Because without it, you have a parallel system of record. Activities don't show up on the account. AEs see "new meeting" with no context. Marketing can't attribute pipeline. Reporting becomes a spreadsheet. Real CRM integration pushes every send, open, reply, and meeting into the contact and account records, with the original AI-generated email body attached for context.
What human-in-the-loop controls should the platform offer?
- Draft review queue. Sample any % of outgoing emails for human approval before send.
- Reply approval mode. Require human sign-off on positive-reply auto-responses.
- Suppression overrides. Block specific domains, contacts, or job titles globally.
- Prompt and ICP versioning. Roll back if a change degrades output.
- Audit log. Every AI decision traceable to its inputs.
Which features are oversold and don't actually matter?
- "Voice cloning" for cold calls. Mostly demos better than it performs.
- "Real-time intent triggers" that fire on every news event. Signal-to-noise is bad without filtering.
- "AI that learns your style." In practice, this is fine-tuning on a tiny sample and doesn't generalize.
- "Unlimited sends." Bounded by deliverability, not by license.
- "100+ integrations." You'll use three. Verify those work.
Common mistakes when scoring AI SDR features
- Buying on demo polish instead of asking for output on your data.
- Confusing "AI-powered" with "AI SDR".
- Ignoring the deliverability layer because it's boring.
- Trusting the vendor's default reply classification without testing it.
- Skipping the CRM integration check until contract is signed.
How SendroAI maps to these must-have features
SendroAI ships all seven by design: AI Research Engine for per-prospect research, A–Z Testing for individualized copy, Automated Sequencing for multi-channel orchestration, Inbox Rotation for deliverability, classified reply routing for handoff, native CRM integration, and human-in-the-loop controls at every step.