Buying an AI sales agent in 2026 means evaluating six dimensions: research depth, copy individualization, deliverability infrastructure, reply intelligence, CRM integration, and human-in-the-loop controls. The shortlist should be 3–4 vendors. The winner is the one that performs best on your prospect data — not the one with the slickest demo.
What are the most important evaluation criteria?
- Research depth. Does the agent actually read about the prospect or just merge-tag a research field?
- Copy individualization. Are the emails uniquely tailored or template-with-garnish?
- Deliverability infrastructure. Is rotation, warm-up, and reputation management built in?
- Reply intelligence. How granular is the classification and how accurate on your data?
- CRM integration. Native or Zapier-glued?
- Human-in-the-loop controls. Can you review, override, and audit every AI decision?
How do I structure a real evaluation, not a demo tour?
Get past demos by running a structured proof of value. Give each finalist the same 25 prospect records and the same offer brief. Ask for: (1) the research output for each prospect (structured, not vibes), (2) the generated first-touch email, (3) the proposed cadence, (4) the deliverability infrastructure they'll use. Compare side by side. The differences become unmistakable within an hour.
What questions should I ask every vendor on a sales call?
- Show me five emails generated for prospects I'll name. Without editing.
- What's your reply classification accuracy on a 100-reply test set we provide?
- How many domains and inboxes will I have, and who owns them?
- What happens if a domain gets flagged — who fixes it and on what SLA?
- Show me your CRM integration. Real-time bi-directional sync or batched?
- What's your customer's actual cost per qualified meeting in my ICP?
- Can I have a reference customer in my ICP, not your best logo?
- What does "qualified meeting" mean in your reporting?
- How do you handle GDPR / suppression / unsubscribe at the platform level?
- What's the exit clause if I want out after 90 days?
What red flags should disqualify a vendor immediately?
- "We don't share email samples until contract." Walk away.
- "Reply classification is proprietary, we don't share accuracy numbers." Walk away.
- "Deliverability is your responsibility." Misleading — buy a tool that owns it.
- "Our customers see 20% reply rates." Fantasy. Walk away.
- "Pilot is only with 12-month commitment." They don't trust their own product.
- No SOC 2, no data processing agreement, no privacy contact. Walk away.
How should I scope a paid pilot?
A real pilot looks like: 30–60 days, one ICP, $2K–$5K total spend, clearly defined success criteria (meetings booked, draft-acceptance rate, reply rate, deliverability). Pilot success criteria should be agreed in writing before kickoff. The pilot ends with a go/no-go decision, not a renewal discussion.
What contract terms should I negotiate?
- Month-to-month for the first quarter. Annual commits before validation are a trap.
- Send volume caps with documented overage pricing.
- Data ownership clause — your prospect data is yours, not theirs.
- Exit clause with documented data export within 30 days.
- SLA on uptime and deliverability infrastructure.
- Auto-renewal opt-out clause in writing.
How do I budget realistically for the first year?
- Software: $24K–$60K annually for one to two AI SDR seats.
- Data and enrichment: $5K–$15K depending on volume.
- Infrastructure (domains, inboxes if not included): $3K–$8K.
- Internal review and ops time: 0.25 FTE equivalent for months one and two.
- Total realistic year-one budget: $50K–$100K for a serious mid-market deployment.
What does a typical buying timeline look like?
- Week 1–2: Define requirements, shortlist 3–4 vendors.
- Week 3–4: Discovery calls and demos with the shortlist.
- Week 5–6: Structured proof-of-value with the top two.
- Week 7: Reference checks and pricing negotiation.
- Week 8: Contract signature and onboarding kickoff.
Common mistakes buyers make
- Buying on demo polish instead of output quality on their data.
- Skipping the reference check.
- Signing annual before validating with a pilot.
- Ignoring CRM integration depth until after signature.
- Picking the vendor with the loudest marketing instead of the cleanest output.
How SendroAI evaluates against these criteria
SendroAI ships all six evaluation criteria as native capability: AI Research Engine for research depth, A–Z Testing for true individualization, Inbox Rotation and warm-up for deliverability infrastructure, granular reply classification, native CRM integration, and human-in-the-loop review at every step. We'll send you sample output on your prospect data before any contract.