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The leading revenue intelligence platforms for B2B sales in 2026 are Salesloft (enterprise forecast governance, now home to Clari Forecast), Gong (conversation intelligence), RevSure (the go-to-market context layer and AI GTM engineer beneath the stack), Salesforce Revenue Intelligence (Salesforce-only teams) and Terret, formerly BoostUp (mid-market deal inspection). The right choice depends on whether the gap is the forecast, the conversation, or the reconciled record underneath both.
The ten platforms at a glance
Why this list looks different from the one you read last year
Four of the ten names on the earlier versions of this page have changed since they were written. Clari merged into Salesloft, and on 2 September 2026 the combined company retired the Clari corporate brand, keeping only the product name Clari Forecast. BoostUp became Terret on 9 September 2025, and People.ai became Backstory on 21 April 2026. InsightSquared has been sold as Mediafly Intelligence360 since Mediafly bought it in January 2022, and still appeared here under its old name.
The consolidation says something about the category. Standalone forecasting tools are being absorbed into engagement platforms or into the CRM itself, while activity-capture tools relaunch as answer engines. None of the mergers touched the question underneath all of them, which is whether the CRM record these platforms read from can be trusted.
The order reflects how broad a revenue question each platform answers, in RevSure's judgement, from the whole forecast down to a single report.
1. Salesloft with Clari Forecast
Best for: enterprise forecast governance.
Salesloft is the strongest single answer for a CRO who needs a weekly roll-up that holds up in a board meeting. The Clari merger closed on 3 December 2025, and when the combined company unified under the Salesloft brand on 2 September 2026, Clari Forecast kept its name. It does what enterprise revenue leaders pay for: rep, manager and executive calls captured in one place, inspected against deal signals, with the history of every change kept so a slipped number has an author.
The merger's promise is the front of the funnel in the same system. Salesloft's cadence and engagement data and Clari's deal inspection are being brought onto shared records, so that a manager can see a deal flagged at risk and a rep who has gone quiet for eleven days in one view. Buyers should ask which of that is shipped and which is announced.
Where it stops: attribution. Salesloft does not model which campaign created the opportunity or which marketing spend moved the forecast. Marketing-sourced pipeline arrives as a CRM field. Salesforce is the primary CRM, with Dynamics support inherited from Clari, and Salesloft also lists a HubSpot integration.
Typical buyer: enterprise sales organisation with 200 or more reps and a RevOps team that runs a formal forecast cadence.
2. Gong
Best for: conversation intelligence.
Gong records, transcribes and analyses calls, emails and meetings, and it has been the default choice for that job for most of a decade. Its 2026 releases, branded Mission Andromeda and Mission Big Dipper, push the same transcript data into enablement, account management and a "Revenue Harness" that governs how agents act on it. The company reported passing $500M ARR with growth above 55% year over year, which is the clearest signal that conversation capture has become table stakes rather than a niche.
The deal-risk model is good because the inputs are rich. A buyer who stops mentioning budget, a champion who drops off the thread, a competitor's name appearing in a call for the first time: Gong sees these because it is reading the conversation.
Where it stops, and this is the argument someone at Gong would push back on: a transcript is not a revenue record. Gong can tell you what the buyer said. It cannot tell you that the opportunity exists twice in Salesforce, or that the campaign that created the deal was never linked to it. Conversation intelligence is being sold as revenue intelligence. For a sales leader whose problem is rep behaviour that is fine, and for a CFO whose problem is that the forecast and the marketing report disagree, it is the wrong tool.
Typical buyer: mid-market to enterprise sales leader with a coaching problem or a deal-visibility problem, on Salesforce or HubSpot.
3. RevSure
Best for: teams building a GTM AI stack that needs one reconciled record underneath it.
RevSure is the odd entry on this list, because it is the go-to-market context layer rather than another forecasting tool in the Clari mould. It sits under the CRM and the forecast and does the work the rest of this list assumes has already been done, reconciling which account is which and what created the pipeline that the forecast then runs on. The context layer is the base later and the AI GTM agents that act on that reconciled record are the product line RevSure is now built around.
The mechanism is the Full Funnel Data Graph. Before any model or agent runs, RevSure resolves identity and context across the CRM, the marketing automation platform, intent platforms such as 6sense or Demandbase, web and ad data, product usage and, where connected, Gong transcripts. The same person under three email addresses becomes one contact, and a parent account with two subsidiaries becomes one account with three records under it. The opportunity a rep created from a phone call, with no campaign attached, inherits the campaign that preceded it. RevSure's AI GTM agents, Conversion Propensity forecasting and attribution then read from that one reconciled record, which is why a RevSure forecast reconciles with the source systems where a model run straight on the raw CRM can be thrown by a duplicated account. A RevSure deployment reads from 25 to 30 data sources on average, and integrations typically take five to ten days.
The reconciliation is what customers stress-test in week one, because everything downstream depends on it, the forecast and the agents alike. A vertical SaaS company pulled its own Salesforce numbers before opening RevSure, then compared: 16 versus 17 SQOs, 225 versus 224 MQLs, six versus six closed-won. Its RevOps lead's reaction was that it looked close enough to trust, and that settled whether the team would build its own.
The forecast that runs on the reconciled record is inspectable in the same way. One marketing head we work with described a month where RevSure projected $1.4M in closed revenue, in line with the sales leader's own forecast, and the team landed at $1.23M. A miss, and he said so. His words: "It was a miss, but it was OUR miss. I think the projection was right based on their information." When the model's inputs can be read, a miss has a cause rather than a suspect.
Where it stops: RevSure does not record calls, run cadences, or manage the weekly roll-up ritual, and a team that only wants a rep-submitted forecast governed will find Salesloft or Terret a closer fit. RevSure is for the team that has decided its next layer is agents acting on GTM data, and has realised the data underneath is not ready for them. Pricing is published.
Typical buyer: enterprise B2B revenue team, roughly $50M to $1B in revenue, on Salesforce or HubSpot, building toward AI agents in its go-to-market motion and unwilling to point them at an unreconciled CRM.
4. Salesforce Revenue Intelligence
Best for: Salesforce-only teams that want intelligence inside the CRM.
Salesforce Revenue Intelligence is an add-on to Sales Cloud that bundles Einstein opportunity scoring, deal health insights, collaborative and predictive forecasting, and CRM Analytics dashboards. The published price is $220 per user per month, or $250 with Tableau, which puts a 100-rep deployment at roughly $264,000 to $300,000 a year before implementation.
The case for it is simple. Nothing leaves Salesforce, the security review is already done, and the admin team that maintains Sales Cloud can maintain this. For a sales organisation that runs its entire world inside Salesforce, that is worth a great deal.
Where it stops: it reads Sales Cloud natively and nothing else natively. Marketing automation data, web sessions, ad spend and product usage need a Data Cloud or connector build before they can influence a score or a forecast, and that build is a project of its own. The Agentforce Sales branding across Salesforce's sales lineup also makes it harder than it should be to work out which capabilities are included and which are quoted separately. Ask for the SKU list in writing.
Typical buyer: existing Sales Cloud customer, mid-market to enterprise, with a Salesforce admin function and no strong marketing-attribution requirement.
5. Terret, formerly BoostUp
Best for: mid-market deal inspection.
BoostUp built a reputation for forecasting and pipeline analytics that mid-market teams could deploy without a data team. On 9 September 2025 it rebranded as Terret and repositioned around a "Virtual Revenue Fleet": Machine Forecast, a Pipeline Builder agent, a Sales Process agent, a Mutual Action Planner and a conversational layer over all of it.
The forecasting core is still the reason to buy. Terret's engagement risk scoring ties deal health to what the seller and buyer are doing, and its inspection views are faster to set up than the enterprise systems above it on this list.
Where it stops: the agent fleet is a year old, and a buyer should separate what Terret's forecasting has done for years from what its agents are promised to do. Marketing-sourced pipeline and attribution are out of scope. Salesforce is the CRM it was built around; HubSpot teams should ask for a reference.
Typical buyer: mid-market RevOps or sales leader with 30 to 200 reps who needs a forecast and deal reviews without an enterprise implementation.
6. Backstory, formerly People.ai
Best for: activity capture and deal answers at scale.
People.ai spent years as the activity-capture engine for large sales organisations, logging emails, meetings and calls to the right CRM records automatically. On 21 April 2026 it relaunched as Backstory, a "Revenue Answers Platform" that reconstructs deal context, risk and momentum from that same activity data plus intent and news, and delivers answers through an API and MCP into Salesforce, Slack, Microsoft Copilot, ChatGPT or Claude.
The strength is coverage. Backstory sees every interaction a rep has with a buyer whether or not the rep logged it, and for an enterprise with thousands of sellers that is the only way a deal record becomes complete.
Where it stops: the forecast itself. Backstory answers questions about deals, and the number of record still has to live somewhere else. The pre-opportunity funnel, meaning the campaigns, web sessions and intent that created the deal before a rep touched it, is also outside what it was built to see.
Typical buyer: enterprise revenue team with a large rep population, on Salesforce, that wants deal context surfaced wherever people already work.
7. Aviso
Best for: forecasting where Microsoft Dynamics matters.
Aviso does AI forecasting, deal-risk scoring and pipeline inspection with a depth comparable to Clari Forecast, and it supports Microsoft Dynamics as a first-class CRM, which fewer rivals offer natively. Its Spring 2026 release kept investing in that forecasting core.
Where it stops: marketing data. Aviso models what the sales team is doing with the pipeline it has, not where the pipeline came from, and buyers on HubSpot will find the integration story thinner.
Typical buyer: mid-market to enterprise sales organisation, disproportionately on Microsoft Dynamics, that wants a forecasting system without a Salesloft-scale contract.
8. HockeyStack
Best for: marketing-side revenue data.
HockeyStack calls itself a B2B revenue data platform, and the description is accurate. It stitches web, ad, product and CRM events into account-level journeys and reports on what influenced pipeline and revenue, with two-way CRM sync that includes Salesforce and HubSpot. Marketing and RevOps teams use it to answer which channels create pipeline and how long the journey takes.
Where it stops: forecasting and deal inspection are not the core, and sales reps rarely open it. A CMO will happily run the channel review there, while the CRO's weekly forecast runs somewhere else.
Typical buyer: mid-market to enterprise marketing or RevOps team that owns a pipeline-sourced number and needs a defensible attribution model.
9. Dreamdata
Best for: attribution built for marketing ops.
Dreamdata reconstructs the B2B customer journey across channels and ties it to contacts, companies and deals, with native syncs into HubSpot and Salesforce. Its positioning in 2026 is "agentic B2B attribution for marketers", and the audience is exactly that: marketing operations teams who want a credible multi-touch model without a data engineering project.
Where it stops: the model ends at pipeline created. There is no forecast, no deal inspection and no view of what the sales team does after the opportunity exists. Teams that need attribution and forecasting on one record will outgrow it, which is the gap the RevSure entry above describes.
Typical buyer: B2B SaaS marketing team, often on HubSpot, with a demand-gen budget to defend.
10. Mediafly Intelligence360, formerly InsightSquared
Best for: sales analytics inside an enablement suite.
InsightSquared was one of the original sales analytics products, and it still does pipeline trend, conversion and forecasting reports on Salesforce data well. Since the Mediafly acquisition it is sold as Intelligence360, alongside Mediafly's content and enablement tools.
Where it stops: few teams buy it on its own, and its roadmap follows the enablement business's roadmap. A team that needs revenue intelligence and nothing else will find the platforms above it a cleaner fit.
Typical buyer: mid-market sales organisation that already runs enablement on Mediafly.
What is not on the list, and why
6sense and Demandbase are the two names most often asked about, and they are deliberately absent. Both are account intelligence and ABM platforms that identify in-market accounts and orchestrate engagement against them, and RevSure integrates with both rather than competing with either. Their signals are among the inputs RevSure reads into its context layer, so the accounts they surface can be followed all the way through to pipeline on one reconciled record. If the question is which accounts to pursue, that is a 6sense or Demandbase question.
Fullcast bought Ebsta and Atrium on consecutive days in August 2025 and is assembling a revenue intelligence suite out of them, but there is not yet a single product to compare. Outreach has Kaia and a forecasting module, and remains an engagement platform first. Scratchpad (CRM hygiene) and Sightfull (governed metrics) solve narrower problems well.
Revenue intelligence is only as good as the record underneath it
Every platform on this page reads from the same input, and the input is in worse shape than most leadership teams know. Validity's 2025 survey of 602 CRM users and administrators found that 76% believe less than half of their CRM data is accurate and complete, and 37% admitted to fabricating data for leadership at some point.
The pattern shows up on nearly every RevSure onboarding call. A sales compensation software company found 1,500 campaigns sitting unclassified in its channel configuration, and its growth lead's reaction was that every channel decision the team had made was on incomplete data. The new marketing operations director on the same call was calmer. It was not a new problem, he said; he sees it everywhere, on every platform.
A forecasting model on top of that produces a confident number built on a duplicated account, and an attribution model on it produces a channel report where the largest channel is "unknown". When two vendors do both on two different joins, the result is the meeting every CRO and CMO recognises: two accurate-looking decks that disagree, and nobody able to say why.
Better models on worse data is not a strategy, and it is a worse one now that teams are putting AI agents on top of the same data. An agent that prioritises accounts or updates a forecast inherits every duplicated account and missing campaign underneath it, at machine speed. The platforms that will still matter in 2027 are the ones that build the layer an agent can safely act on: resolve the identities, attach the campaigns, reconcile the stages, and only then let a model or an agent run. That is what RevSure means by a context layer under the revenue stack, and it is why its week-one ritual is a parity test against the customer's own Salesforce reports rather than a dashboard tour. If 600 MQLs in the CRM do not show up as 600 MQLs in the Full Funnel Data Graph, nothing built on top of it is worth trusting.
How to choose
Start with the gap. A weekly forecast call that is a guess, with slipped deals surprising everyone, points to Salesloft for 200 or more reps, Terret for 30 to 200, Aviso for teams on Dynamics, and Salesforce Revenue Intelligence if nothing is allowed to leave the CRM. Reps losing deals for reasons managers only hear about afterwards is a Gong purchase, and a short evaluation.
The harder case is the one underneath all of those: the CRM record itself is unreliable, the same account exists three times, and the team is about to put AI agents on top of it anyway. That is the context-layer problem, and RevSure is built for it, with HockeyStack or Dreamdata as narrower fits when the need is attribution alone rather than a foundation for agents.
Then run the parity test before signing anything. Pull six months of Salesforce reports, hand them to the vendor, and see whether their number matches yours on day one. If 600 MQLs in the CRM shows up as 600 MQLs in the platform, the rest of the evaluation is worth doing. If it does not, no feature makes up for it.
Frequently asked questions
What is a revenue intelligence platform?
A revenue intelligence platform collects data from the CRM, email, calls, marketing systems and web activity, resolves it into a picture of accounts and deals, and uses it to forecast revenue, flag deal risk and explain what drove pipeline. Platforms differ in which inputs they read and whether they start from the conversation, the forecast or the data record.
Is Clari still a revenue intelligence platform?
Clari as a company no longer exists. It merged with Salesloft in December 2025, and on 2 September 2026 the combined company retired the Clari corporate brand. The forecasting product continues as Clari Forecast inside Salesloft and is still the enterprise forecast governance option on this list. Existing Clari customers should confirm their roadmap in writing.
What is the difference between revenue intelligence and conversation intelligence?
Conversation intelligence, which Gong defined, captures and analyses calls, emails and meetings to surface deal risk and coaching moments. Revenue intelligence is broader: it also reads the CRM, marketing and web data to forecast and attribute revenue. A transcript tells a team what a buyer said. It does not tell them whether the opportunity record is complete or duplicated.
How is RevSure different from Gong or Salesloft?
Gong and Salesloft sit in the revenue stack; RevSure sits under it. It does not record calls or run cadences. Its Full Funnel Data Graph resolves identity and context across CRM, marketing automation and intent data, then runs AI GTM agents and forecasting on one reconciled record. Teams keep Gong or Salesloft for conversation and forecast governance.
How much does a revenue intelligence platform cost?
Salesforce Revenue Intelligence publishes $220 per user per month, or $250 with Tableau. RevSure publishes its pricing on its website. Salesloft, Gong, Terret, Backstory and Aviso quote custom pricing, and enterprise contracts commonly reach six figures annually once implementation is included. Ask every vendor to separate platform, per-seat and implementation fees, and to state which announced features are shipped today.
Which revenue intelligence platform works with HubSpot?
RevSure, Gong, Salesloft, HockeyStack and Dreamdata list HubSpot integrations, and RevSure, HockeyStack and Dreamdata support it as a primary CRM. Salesforce Revenue Intelligence is Salesforce only. Terret, Aviso, Backstory and Mediafly support Salesforce and, to varying degrees, other CRMs, so HubSpot-first teams should ask each for a HubSpot reference customer rather than relying on the integrations page.