What should you look for in an AI SDR tool?
Five checks, in this order: where the approval gate sits, whether limits are enforced or merely suggested, what happens when a cap is reached, whether the vendor publishes how it measures account health, and whose data the leads come from. A ranked list ages badly. A rubric you can run yourself does not.
Why this is a rubric and not a ranking
We have not verified most competitor claims, so we are not going to rank them. Where a company has published its own scale, we will repeat it as published and no further: HeyReach around $10M ARR, Waalaxy around EUR 10M across 150K users and 10K paying, Expandi around $10M, lemlist around $53M, and Linked Helper reporting 500K+ users since 2016.
Those figures describe company size, not whether a product will protect your account. A ranking is also stale the month after it goes up. The five checks below you can run yourself, on a demo call, against any vendor including this one.
One more reason to run the checks yourself: what actually separates these products is almost never in the feature comparison. Two tools with identical feature lists can behave completely differently when a limit is reached or a session expires, and that behaviour is what you will live with daily. Feature parity is easy to reach and tells you close to nothing.
Check one: where the approval gate sits
Ask to be shown the screen where a message is approved before it leaves. Then ask two follow-ups: can the gate be switched off, and is it off by default.
Three configurations are honestly defensible for some buyer: every send approved, a review queue that can be bypassed, and fully autonomous. What is not defensible is a vendor who cannot show you the screen at all, because it means review was never designed in and you will end up reviewing nothing.
While the screen is open, look at what the approval actually shows you. A gate that displays the message and nothing else is thinner than it appears. You want the recipient, the reason they are on the list, and the history with them, because approving a message without those is approving a sentence rather than a decision.
Check two: enforced or suggested limits, and what happens at the cap
A limit you type into a settings field is a suggestion you make to yourself at your most optimistic. A limit enforced server-side is a limit. Ask which one you are looking at, and ask who inside the vendor can raise it.
Then ask the sharper question: what happens when the cap is reached. There are three behaviours. It refuses and tells you. It queues and sends tomorrow. Or it overshoots and reports success. The third is the one that costs you an account, and it will not be in the marketing page.
Ours refuse. A new seat runs at 20 invitations a day and 80 a week with a ramp of 0.5x in week zero, 0.75x in week one and 1.0x from week two. Worth knowing while you ask: LinkedIn publishes no invitation limit at all, so a vendor quoting you a precise official number, daily or weekly, is quoting something LinkedIn never said.
Check three: does the vendor publish account-health methodology
Ban rates get advertised constantly and defined almost never. Ask for three things: the denominator, the time window, and the date of measurement. A percentage without those is a marketing line, and a vendor who cannot produce them on request does not have them.
We hold ourselves to the same test rather than exempting ourselves from it. We measure restrictions per managed seat per rolling 90 days, and while the denominator is still small we publish the methodology instead of a number we could not defend if you pushed on it.
Ask one adjacent question too: what does the tool do when an account is restricted. A vendor who has thought about account health has an answer about pausing, diagnosing and resuming. A vendor who has not will tell you it does not happen, which is the least believable sentence anyone says in this category.
Check four: whose data is it
A bundled contact database is convenient, and it transfers a problem to you. Staleness you cannot audit, provenance you cannot prove, and data-protection exposure under GDPR and DPDP that the buyer inherits rather than the vendor.
So ask where each lead came from, and whether you could give that answer to a regulator with a straight face. Our sourcing is your own LinkedIn seat plus your own CSV imports, because that question has a clean answer and a bundled database does not.
The same question applies on the way out. Ask whether you can export your lead data, your message history and your contacted list when you leave. A product whose core asset is the memory of who you have already contacted has natural lock-in, and you want that stated up front rather than discovered at the point you want to go.
Check five: which integrations actually exist today
Ask which integrations are shipped, which are in limited testing, and which live on a roadmap slide, then ask for that in writing. The gap between those three categories is where most post-purchase disappointment comes from.
Ours, stated plainly: there are no CRM, Zapier, HubSpot, Salesforce or webhook tools in this build. Claude is first-class today across claude.ai, Desktop and Claude Code, and ChatGPT and Cursor are roadmap. If a CRM write-back is a requirement, we fail this check, and you should find that out before a trial rather than during one.
Finally, ask what the tool does not do, and watch how the answer is delivered. Every product has a scope edge. A vendor who names theirs quickly has thought about who they are not for. A vendor whose answer to every requirement is yes is either selling a roadmap slide or has not understood the question.
The five checks, and what a weak answer sounds like
| Check | Strong answer | Weak answer |
|---|---|---|
| Approval gate | They show you the screen and name the default | "It runs autonomously", with no review surface |
| Limits | Enforced server-side, nobody raises them in-app | A number you type into a settings field |
| At the cap | It refuses and tells you | It queues quietly, or overshoots and reports success |
| Account health | Denominator, window and date of measurement | A ban-rate percentage with no methodology |
| Sourcing | Your own seat and your own imports | A bundled database with unclear provenance |
Questions people ask next
What is the best AI SDR tool?
We will not rank tools we have not verified. Judge any vendor on five checks: where the approval gate sits, whether limits are enforced, what happens at the cap, whether account-health methodology is published, and whose data the leads come from.
What should I ask on an AI SDR demo?
Show me the approval screen. Can I raise the limit. What happens when the cap is hit. What is the denominator on your ban rate. Where did this specific lead come from.
Are enforced limits worse than configurable ones?
They are less flexible, and that is the point. A cap earns its keep by refusing at the exact moment you would have chosen to raise it.
Does a higher ARR mean a better product?
No. Published ARR describes company scale. It says nothing about whether a product protects the account you are running it on.
Why this page exists: Buyer questions collected from r/AskGTM and r/gtmengineering AI SDR threads, 2026
LinkedBoost is the LinkedIn MCP server: your agent sources, drafts, sends and works the inbox, inside caps the server enforces rather than suggests.
Related answers
Fully autonomous AI SDRs mostly did not hold. The teams still getting value moved the agent from decision-maker to operator: it researches, drafts and paces, a human approves, and volume stayed where a human could review it. The failure was never the writing.
Because the bill arrived before the pipeline did. Contracts were signed on a promise measured in quarters, while the cost, in account standing and recipient goodwill, was spent in weeks. The deployments that renewed kept a human on the approval gate, volume small enough to review, and targeting nobody outsourced.