Convin pricing, features and alternatives

The short answer

Buy Convin if you run a contact center or inside sales floor where QA samples calls by hand, agents handle similar conversations repeatedly, and team leads already have coaching time set aside. Reviewers call out quick setup and straightforward CRM integration, and several name the support team as the reason their account stayed.

Skip it if you have no defined QA criteria yet, because automated scoring needs a standard to score against and calibration will consume the hours you hoped to save. Skip it too if you sell long, multi-stakeholder enterprise deals: that is deal inspection, and Gong is built for it at a quote-only price of its own.

Where Convin fits

Convin fits a floor rather than a sales team: many agents, repeatable conversations, and a shared scorecard that is supposed to apply to all of them. The product analyzes both calls and chats, scores them against quality criteria automatically, and routes the behaviors tied to good and bad outcomes into coaching. That is a QA and agent-behavior argument, not a deal-strategy one, and the distinction decides whether the purchase makes sense before any price is discussed.

The prerequisite buyers underestimate is the scorecard itself. Automated scoring is only as useful as its match with your criteria, so a team that reviews calls on instinct has nothing for Convin to automate. Write the criteria down first, with the weightings and the pass bar, and keep a batch of hand-scored calls as your control set. Our sales call scorecard is the dull version of that work, and it is what turns a pilot into a measurement instead of an impression.

Settle which product you are buying before the demo, because Convin's pricing page groups it into four suites and a rep can show you all of them. There is CX with AI phone calls, Real-Time agent and supervisor assist, Voice of Customer analytics, and Post Interaction QA with coaching and an LMS. A QA leader replacing manual review wants the last one. An operations leader who wants prompts delivered while the agent is still on the call wants the real-time suite, which is the same job Balto sells against. Those are different budgets and different rollouts, and a blended quote hides which one you are paying for.

If your conversations are long, complex B2B deals, this is the wrong shelf of the catalogue. Deal-focused tools compute risk and forecast from opportunity records rather than scoring agent behavior, which is why buyers in that situation end up running Clari against Gong or Gong against Chorus instead. The direct Convin comparison is Observe.AI, which sits in the same contact-center QA bracket and is also quote-only. Both of them live in our conversation intelligence software directory, and the coaching end of the job overlaps our sales coaching software directory.

Call recordings are customer data, so security review is part of the evaluation rather than a formality after it. Convin stores conversations so it can score them, and buyers in this category routinely ask for certifications, retention policy and deletion behavior in writing. Ask what happens to transcripts if you do not renew, and run the request through our vendor security review checklist rather than through a sales email thread. Transcription accuracy on your own languages and accents belongs in the same conversation, because a score computed from a bad transcript is confidently wrong rather than roughly right.

Convin pricing

Convin publishes no paid prices. Our September 2026 check of its pricing page found the product grouped into four suites, CX with AI phone calls, Real-Time agent and supervisor assist, Voice of Customer analytics, and Post Interaction QA with coaching and an LMS, each routed to a demo request. One item is marked free: a single manual QA platform for teams that only need to score calls by hand. That free product is worth knowing about, because it is the manual process Convin's paid automation is meant to replace, not a cut-down version of it.

What the pricing page lists

Quality Management (manual QA)

Free. A single manual QA platform for teams that score calls by hand. No automated scoring, which is the part you would be buying.

CX, Real-Time, Voice of Customer, Post Interaction

Custom quote at every suite. Nothing published. Expect agent count and the volume of conversations analyzed to be the two variables that set the number.

Bring two numbers to the first call, your agent count and your monthly conversation volume, then ask about the rest of these before a proposal is drafted.

1. Agent count, which is the variable buyers model and the one that tells you least about the total.
2. The volume of conversations analyzed, since contact-center quotes usually ride on throughput rather than on headcount alone.
3. Whether call analysis and chat analysis are priced separately. A floor that handles both can find it has bought scoring for one channel.
4. Whether AI phone calls are billed per minute. A per-minute line behaves nothing like a per-agent line once volume moves.
5. Whether historical conversations count against your volume when you first load data. A backfill of last year's calls can consume the allowance you bought for this year's.
6. Which suites are in scope, priced one at a time rather than blended. Post Interaction QA and Real-Time assist solve different problems and only one of them is usually the reason you called.
7. The contract term and what happens to your stored transcripts if you do not renew.

Because the value case rests on replacing manual QA hours, build the anchor yourself before the first call: count the reviewers, the hours each spends scoring, and the share of conversations that gets reviewed at all. That total is your negotiating position and your break-even, and our sales tool ROI calculator is where to put it next to the licence line. Then get the per-suite price, the volume definition and the renewal terms in writing, since a quote-only vendor cannot be price-compared on a spreadsheet until you hold two proposals at once. Read how we review software for what we verify and what we leave to your procurement team.

What Convin gives up

You give up knowing what it costs before you talk to a salesperson. Four suites, two pricing variables and no published rate means the first proposal is an opening position rather than a price. Run a competing quote in parallel, ask for each suite priced on its own, and treat the blended number in the first deck as the thing you are negotiating away from.

You give up trusting the scores on day one. Automated QA needs tuning to your criteria, and managers will not coach from a number they do not believe. Expect calibration time as a real line in the project plan: score a batch by hand, compare it against Convin's output, and keep adjusting until a team lead would defend the result to the agent in the room. If the two never converge, the automation has not saved the hours the business case promised.

You give up enterprise deal depth. Convin is built around agent behavior at scale, so sales-specific features are lighter here than in deal-focused tools, and a team running six-month pursuits with five stakeholders will find the scorecard model a poor fit for what it needs to inspect. That is an orientation rather than a defect, and it is the single most common reason a shortlist should not include Convin at all.

You give up the free tier the moment automation is the point. The one free item is a manual QA platform, so it buys you a place to run the process you already run rather than a preview of the product you are evaluating. Use it to formalise the scorecard if you have not, then accept that the question the free tier cannot answer is the only question that matters.

You give up self-serve answers on security. Convin holds recordings and transcripts of customer conversations, and the documentation that proves how it handles them arrives on request rather than on the website. Involve your security team before the pilot rather than after it, get retention, deletion and export behavior in the contract, and remember that an archive of customer calls you cannot export is a switching cost rather than an asset.

How Convin compares

Three of the five options below refuse to publish a price, which is normal for software sold into contact centers and worth knowing before you budget. The split that decides the shortlist is not feature depth: it is whether you are scoring agent behavior or inspecting deals, and whether the help needs to arrive during the call or after it. Convin and Observe.AI compete directly on automated QA across a high-volume floor. Balto competes on the real-time end, prompting an agent while the conversation is still live, which is a different rollout and a different change-management problem. Gong competes where the unit of analysis is an opportunity rather than an agent, and it is quote-only for the same structural reasons. Avoma is the honest answer for a team that wanted meeting notes and light coaching rather than QA at scale, and it publishes rates, which means you can compare it on a spreadsheet instead of a call. Read the last column twice. All five break somewhere, and the only question that matters is whether each one breaks where your team works.

What to test in a Convin pilot

There is no self-serve route to the automation, so scope the pilot yourself and run it on one team with real recordings rather than on a sample dataset. Every step below exists to produce a number you can put in a business case, and the number that decides the purchase is agreement between Convin's scores and your reviewers'.

1. Load your existing QA scorecard, criteria and weightings included, and find out what does not map. The gaps are where calibration time goes.
2. Hand-score a batch of 50 recent calls first, then run the same batch through Convin and count the disagreements. Rate of disagreement, not average score, is the result you report.
3. Have your best reviewer adjudicate twenty of the disagreements. If Convin is right more often than the reviewer expected, you have a coaching tool. If not, you have a dashboard.
4. Test transcription on your actual languages and accents, including your noisiest line and your fastest talker, and ask how accuracy is measured rather than accepting that it is high.
5. Take one flagged call all the way through to a coaching session with a team lead, and ask the lead afterwards whether they would do it again unprompted. Then check what the platform records about progress after the session.
6. Connect your production CRM and confirm which fields write back, since reviewers credit the integration as easy and easy is not the same as configured.
7. Measure the manual hours the pilot team saved over a fortnight and multiply out to the floor. That figure, against the quote, is the whole business case.
8. Get the commercial answers in writing during the pilot: price per suite, how conversations are counted, whether chats and AI calls are billed separately, and your export rights on transcripts if you do not renew.

Convin questions buyers ask

What is Convin used for?

Convin automates quality assurance and coaching by analyzing calls and chats. Contact centers and high-volume sales teams use it to review every conversation instead of a sample.

Is Convin good for sales teams?

It suits high-volume sales teams with repeatable calls, such as inside sales or telesales. Enterprise teams running long, multi-stakeholder deals may be better served by deal-focused conversation intelligence.

Is Convin a reliable platform?

Reviews are generally positive about ease of use and support. Reliability for your team depends on transcription accuracy on your calls, so test it with real recordings during evaluation.

How secure is Convin?

Ask Convin for its security documentation, certifications, and data retention policies. Call recordings contain customer data, so involve your security team early.

How much does Convin cost?

Convin does not publish prices for its paid suites. Its pricing page lists a free manual QA tool; automated QA, agent assist and AI calling are quoted, usually on agent count and conversation volume.

What is Convin AI?

Convin AI is the analysis layer inside Convin: it transcribes calls and chats, scores them against your quality criteria, flags the agent behaviors tied to good and bad outcomes, and powers the real-time assist and AI phone call suites. The scoring has to be calibrated against your own reviewers before managers will trust it.

How does conversational AI work?

Conversational AI tools transcribe a call or chat, then evaluate the transcript against criteria you define, producing a score, a sentiment reading and flagged moments. Accuracy depends on the transcript, so test it on your own accents and line quality. Our conversation intelligence glossary entry covers the category in more detail.

Related

If Convin is on your shortlist, the comparisons worth running are Observe.AI for the same contact-center QA job, Balto where the guidance has to arrive mid-call, and Gong where the unit of analysis is a deal rather than an agent. The full set sits in our conversation intelligence software directory, the coaching end overlaps sales coaching software, and our sales call scorecard is the document that makes the pilot measurable instead of anecdotal.

Convin sits in our Conversation Intelligence Software directory.