Why Airspeed
Why teams switch to Airspeed
Intelligence
See which deals are real
Airspeed reads the whole conversation, not just keywords, and turns it into structured deal and revenue intelligence. You see which deals are real and which are quietly slipping.
Agents
Agents do the busywork
The recap, the CRM update, the follow-up draft: Airspeed agents run the post-call work in minutes, so reps stay in the deal instead of the data entry.
Coaching
Coaching on every call
Every rep scored on every call, automatically, against the moments that actually win deals. No manager staying late to review recordings.
CRM automation
Your CRM fills itself
Fields, notes, and next steps written back to Salesforce or HubSpot after every call, with dynamic mapping to your own fields.
Forecasting
Forecasts built on what buyers said
Every deal gets an AI close probability grounded in the calls themselves, rolled up into team forecasts you can defend. Commit, best case, and pipeline in one live view.
What to watch for
Your forecast is wrong because deal stages, close dates, and qualification are self-reported and rarely updated. The data is broken before the math runs
You pay for a forecasting suite, but its rollups inherit garbage from a CRM nobody keeps current
Industry surveys put manual or CRM-only forecast accuracy around 60-75%, against roughly 90-98% for AI-assisted forecasting on clean data. The gap is mostly data hygiene, not the model
How did we choose and rank these tools?
We scored each platform against public pricing, vendor documentation, verified user reviews, and hands-on testing. Buyers conflate two jobs in this query: modeling a forecast (rollups, commit, scenario math) and managing the deals and data that feed it. No single product does both equally well, so we name the layer each tool actually owns. Prices are indicative; confirm with each vendor.
- Forecasting depth - rollups, commit/quota workflows, and scenario (what-if) modeling
- Deal management - pipeline inspection, deal-risk signals, and stage governance
- Data accuracy at the source - how clean and structured the CRM fields feeding the forecast actually are
- CRM write-back depth - structured fields and picklists vs. free-text notes or activity logging
- Execution vs. analytics - whether the platform acts on data or only reports it
- Total cost of ownership and fit by team size (SMB, mid-market, enterprise)
Sources: Vendor pricing pages and public reporting, reviewed June 2026; G2 and Capterra reviews; Hands-on product testing by the Airspeed team; Analyst coverage (Forrester and Gartner) for category positioning; Industry surveys on forecast accuracy, 2024-2026 (e.g. Salesforce State of Sales).
8 alternatives, ranked
Airspeed
Forecasts built from call evidence, on CRM data it captures itself
- CRM write-back to any field, including dropdowns and picklists (deal stage, loss reason, qualification status), matched to your existing options. Structured, reportable data, not a free-text notes blob
- Qualification scoring (MEDDIC, MEDDPICC, BANT, SPICED, SPIN) pulled from the conversation, not rep self-report, so it attacks sandbagging and commit inflation at the source
- AI agents (Deal Execution, Insights, Outbound, Coaching) that act on the structured CRM data on their own
Clari
Enterprise forecast rollups, commit management, and pipeline governance
- Deep forecast rollups, commit and quota workflows, and pipeline inspection
- Named category leader in Forrester and Gartner coverage, so a procurement-safe brand
- Deep bidirectional Salesforce integration and automated activity capture
The catchConversation intelligence (Clari Copilot) is an add-on and can lag the specialists
Gong
Conversation-intelligence-driven deal-risk signals and forecasting
- Largest conversation-intelligence dataset in the category, with strong brand recognition
- Deal-risk signals drawn from what was actually said on calls and emails
- Gong Forecast layers AI deal scoring on top of that conversation data
The catchForecasting is an add-on, not the core product, and pricing runs high with multi-year locks
BoostUp (Terret)
Best-value full-stack forecasting and deal management for mid-market
- Full-stack forecasting, pipeline inspection, and deal management in one platform
- Strong value against Clari and Gong for mid-market budgets
- Configurable forecast hierarchies and rollups, with activity capture
The catchSmaller dataset and brand footprint than Gong or Clari
Aviso
Deep predictive and scenario (what-if) forecasting
- Some of the deepest predictive and scenario (what-if) forecast math in the category
- AI deal scoring, pipeline inspection, and a guided-selling assistant
- Strong for teams modeling multiple forecast scenarios and roll-up paths
The catchSmaller brand than Clari or Gong for procurement
Salesforce Sales Cloud (Einstein/Agentforce)
Forecasting native to the CRM you already run
- Forecasting lives inside the CRM, so there is no separate data sync for the model
- Collaborative Forecasts, Einstein deal scoring, and Agentforce agents in one stack
- Scales with the Salesforce governance and permissions you already have
The catchNo native conversation intelligence, so it cannot read your calls
HubSpot Sales Hub
CRM-native all-in-one forecasting and deal management for SMB and mid-market
- Forecasting, deal pipelines, and reporting native to HubSpot, all one system
- Easy to set up and adopt next to the enterprise suites
- Good value for SMB and lower mid-market teams
The catchForecasting is shallower than Clari, Aviso, or BoostUp on complex hierarchies
Oliv AI
Oliv is the Agent OS for revenue teams.
- Modular pricing: buy only the agents you need, with no platform fee on top, so entry cost lands far below the enterprise forecasting suites here.
- The Deal Driver agent writes the follow-up, sends it, and watches for a reply, so deals keep moving between forecast calls.
- Call recording, AI transcription, and CRM auto-sync are in the core product, so deal signals come from captured activity rather than rep entry.
The catchOliv's forecast starts from account memory, not rep-entered fields. The Context Graph keeps each account's story up to date from every call and email: who is involved, what was promised, and what has changed. That lets the CRM Manager agent keep stages and close dates current before the Forecaster agent drafts the number.
Feature by feature
| Feature | Airspeed | Clari | Gong | BoostUp (Terret) | Aviso | Salesforce Sales Cloud (Einstein/Agentforce) | HubSpot Sales Hub | Oliv AI |
|---|---|---|---|---|---|---|---|---|
| Forecast rollups & commit/quota workflows | ✓ | ✓ | Add-on | ✓ | ✓ | ✓ | ✓ | ✓ |
| Scenario / what-if modeling | Launching soon | ✓ | Limited | ✓ | ✓ | Limited | Limited | ✓ |
| Conversation intelligence | ✓ | Add-on | ✓ | ✓ | Limited | ✕ | ✕ | ✓ |
| Structured CRM write-back to picklists/dropdowns | All fields + picklists | Fields, limited picklists | Limited | Limited | Limited | Native fields | Native fields | Deal stage and close date fields |
| Qualification scoring from the conversation | Extracted from calls | ✕ | Infers MEDDIC fields | Partial | Partial | ✕ | ✕ | ✓ |
| Autonomous AI agents that act on CRM data | ✓ | Limited | 18-agent library | ✕ | Guided selling | Agentforce | Breeze | ✓ |
Compared on public pricing, vendor documentation, and verified G2 and Capterra reviews by the Airspeed team. Pricing as of June 2026; confirm current pricing with each vendor. Last verified October 2026.
Airspeed by the numbers
When Clari is still the better pick
- You need enterprise pipeline governance and board-level forecast administration as your system of record. This is Clari's core
- Procurement wants the most recognized name with the largest enterprise install base, and you have a dedicated RevOps team to run it
- You want forecast scenario modeling and inspection workflows owned by one vendor across the full revenue cadence, including the Salesloft engagement tooling now under the same roof
Frequently asked questions
What is the best AI forecasting and deal management tool?
Airspeed, Clari and Gong are the main platforms for forecasting and deal management in one place. Airspeed builds the forecast from what buyers said on calls, with rep submissions, manager rollups, and AI-adjusted calls, and writes the deal fields underneath it to your CRM's real picklists. Clari leads on enterprise pipeline governance and scenario modeling, and Gong on conversation-driven deal-risk signals for large teams with dedicated RevOps. Aviso and BoostUp (Terret) are strong on predictive math, and Salesforce Sales Cloud and HubSpot forecast natively inside the CRM.
Why is my CRM forecast inaccurate?
Because the forecast is only as honest as the data feeding it, and most CRM deal data is self-reported, entered late, and never checked against what was actually said on calls. Industry surveys put manual or CRM-only forecast accuracy around 60-75%. The fix is less about a better model and more about capturing accurate, structured deal stage, close date, and qualification data at the source.
Can AI forecast sales accurately?
Vendor and industry reporting (2024-2026) cites AI-assisted forecasting at roughly 90-98% accuracy, well above manual methods, but that range assumes clean input data. The suites (Clari, Aviso, BoostUp, Gong) supply the predictive engine; the accuracy gain collapses when the CRM fields feeding them are stale or guessed. Pairing a suite with a tool that captures structured CRM data from conversations is how teams reach the top of that range.
How do forecasting suites differ from revenue execution?
Both model a forecast now. A suite (Clari, Aviso, BoostUp, Gong Forecast) runs rollups, commit and quota workflows, and scenario math on pipeline data reps maintain by hand. Airspeed runs the rollups too, with Won, Commit, Best Case, and Pipeline categories, but builds them from call evidence and writes deal stage, loss reason, and qualification to real CRM picklists as it goes. The suites go deeper on scenario modeling and enterprise governance. Airspeed goes deeper on where the numbers come from.
Does Airspeed do forecasting?
Yes. Airspeed AI Forecasting scores every deal on call sentiment, buyer behavior, deal velocity, and MEDDIC completeness, and rolls that into team forecasts with Won, Commit, Best Case, and Pipeline categories, AI-adjusted calls, and early warnings on deals likely to slip. Because Airspeed also writes structured deal data to the CRM automatically after every call, the forecast sits on clean data by default. Teams that need enterprise governance modules or deep scenario modeling as a system of record still pair it with a suite like Clari or Aviso.
How do I choose between these platforms by team size?
Enterprise teams that need forecasting as the system of record should look at Clari (governance and brand) or Aviso (predictive math). Mid-market teams that want full-stack forecasting at a friendlier price should consider BoostUp (Terret). Salesforce-native or HubSpot-native orgs can use their CRM's built-in forecasting. Whichever you pick, mid-market teams (20-200 reps) add Airspeed so the deal data feeding the forecast stays accurate and structured.
Book a demo. See it in action.
Watch Airspeed log the call, update your CRM, and draft the follow-up, in your own pipeline.
Book a Demo
