Aviso

Modules, Agents And Claims

Revenue Intelligence, Summarised

• Aviso is a revenue intelligence platform that forecasts, inspects pipeline and analyses sales conversations for go-to-market teams, now built around AI agents rather than dashboards alone.
• Scale of automation is the pitch: more than 30 prebuilt agentic workflows spanning BDR to CRO, and over 50 task-based agents.
• A no-code GTM Agent Studio lets revenue operations build and deploy agents without engineering, which is the most distinctive thing here.
• Coverage is broad — conversation intelligence, relationship intelligence, coaching, marketing intelligence, sales engagement, forecasting, pipeline inspection, deal acceleration and customer success.
• Forecast accuracy is claimed as nearly 100%, a figure that needs careful reading rather than acceptance.

The Forecast Accuracy Claim Cannot Mean What It Sounds Like

Nearly 100% forecasting accuracy is the headline number and it needs addressing first, because it is the kind of claim that should make a buyer more careful rather than more interested.

Sales forecasting predicts human decisions made by people outside your company. Whether a deal closes depends on a buyer's budget approval, a competitor's counter-offer, an internal reorganisation, a champion leaving, or a procurement process nobody told you about. No model has access to any of that.

So what could the figure plausibly describe? Most likely aggregate accuracy at the quarter level across a whole book of business, where individual deal errors offset each other — some deals slip, others pull forward, and the total lands close. That is a genuine and useful capability, and it is a very different claim from predicting deals.

It might also describe accuracy in the final week of a quarter, when most outcomes are effectively known. Being accurate about a quarter that is nearly over is not the hard part.

The number that would actually be useful is not published anywhere in this category: accuracy at the start of a quarter, measured against outcome, compared against what the sales leader's own manual forecast would have said. That comparison is the whole question and nobody publishes it.

None of this means the forecasting is bad. It means the headline is doing marketing work rather than analytical work, and a buyer should ask what specifically was measured, over what horizon, and against what baseline.

A forecast predicts decisions made by people who do not work for you. Nearly a hundred percent accuracy is not a capability claim — it is a question about what was measured.

Everything Here Depends On CRM Data You May Not Have

This is the dependency that determines whether any revenue intelligence platform works, and it is rarely stated by vendors.

Forecasting, pipeline inspection and deal scoring all reason over your CRM: what stage deals are in, when they were last touched, what the close date says, who is involved. If reps update Salesforce on the Friday before a quarter closes, in a hurry, to whatever keeps their manager quiet, then the platform is reasoning over fiction.

The industry's standing joke about CRM hygiene exists because the problem is universal. Deals sit in stage four for five months. Close dates get pushed rather than re-examined. Contacts are missing. Notes are absent.

There is a genuine counter-argument in Aviso's favour here, and it is the strongest thing in the product's design. Conversation intelligence and relationship intelligence generate their own data rather than depending on rep input. Call recordings and email traffic exist whether or not anyone updates a record, and a platform reading those knows something the CRM does not.

Top-of-funnel agents like Artisan never see this stage at all. Relationship intelligence specifically addresses single-threading — a deal where the rep knows one person and that person leaves. That signal comes from email and calendar patterns, not from a field someone forgot to fill.

So the practical evaluation question is which parts of the platform generate their own data and which parts inherit your CRM's quality. The first group works regardless; the second is only as good as your hygiene, and no vendor can fix that for you.

The Agent Studio Is The Actual Differentiator

Fifty task agents and thirty workflows is a large number and numbers are easy. The no-code studio for building your own is the part that is structurally interesting.

The reason is that sales processes differ enormously between companies in ways software vendors consistently underestimate. Stage definitions, qualification frameworks, approval thresholds, what counts as a commit — all of these are local, and a platform shipping fixed workflows forces you to adopt someone else's assumptions or abandon the feature.

Letting revenue operations build agents without engineering addresses that directly. RevOps teams typically sit close to the process, know exactly where the manual work is, and cannot get engineering time — which is precisely the profile a no-code builder serves.

The prebuilt library then works as a starting point rather than a constraint: take the closest workflow, adapt it to how you actually operate.

The caution is the standard one for no-code agent platforms, and it is worth planning for. Fifty agents that anyone can extend becomes fifty-plus-thirty agents nobody owns within a year. Agents that act on records, send messages or update forecasts need the same governance as any automation — who can create them, who reviews them, what they may touch, and how you turn one off.

Ask specifically what an agent is permitted to do without approval, since the difference between an agent that recommends and one that acts is where the risk lives.

1. Ask what specifically was measured to produce the forecast accuracy figure, and over what horizon.
2. Separate the modules that generate their own data from those that read your CRM.
3. Run the forecast in parallel with your existing process for a full quarter before trusting it.
4. Compare its accuracy against your sales leader's manual call, not against zero.
5. Define agent governance — who builds, who approves, what may act unattended — before the studio is opened up.

Quoted, Not Published

This site does not publish plan prices, and neither does Aviso — the pricing page exists but discloses nothing, which implies contact sales.

In revenue intelligence the quote is almost always per seat, sometimes tiered by which modules are included. Conversation intelligence in particular is frequently priced separately because recording, transcribing and analysing calls carries real cost per user.

The variable to establish early is who counts as a seat. Some platforms charge for every rep whose calls are recorded; others only for people who log in to view analysis. On a large sales floor those two definitions produce very different numbers.

The second question is which modules are in the base. A platform listing eleven modules almost certainly does not include all eleven at the entry tier, and forecasting plus conversation intelligence — the two most people actually want — are commonly split.

The comparison worth running is against Gong and Clari, which occupy the same market with more established positions. Aviso's argument against them is breadth and the agent studio rather than depth in any single module, and that is the axis to test.

For a smaller sales team, the honest framing is that this whole category is priced for organisations with a dedicated revenue operations function. If nobody owns forecasting as a job, the platform will not be adopted regardless of what it costs.

How To Read The Outcome Percentages

Three customer-outcome figures appear and they share the same structural problem, which is worth understanding once and applying to every vendor in this category.

Established incumbents such as Clari publish figures with the same structural problem. 40% increase in average win rate. 70%+ improvement in net new revenue closed per AE. 36% net new revenue increase per rep across customers of a year or more.

The problem is attribution rather than honesty. Companies that buy revenue intelligence platforms are almost never only buying software — they are usually hiring a RevOps leader, tightening stage definitions, introducing deal reviews and improving CRM discipline at the same time. The platform arrives with the reform, and the improvement belongs to all of it.

There is also a selection effect. Organisations willing to invest in this category tend to be growing and professionalising already, so their numbers would likely have improved regardless.

The third figure is the most carefully worded and therefore the most revealing: measured across customers of a year or more. That excludes anyone who churned, which is the group whose results would have pulled the average down.

None of this makes the platform ineffective. It means published percentages in this market describe correlation inside a self-selected sample, and the only number that will tell you anything is your own — measured before you start, against a quarter you actually forecast.

• Buyers typically reform process and hire RevOps at the same time as buying software
• Companies adopting this category are already growing and professionalising
• Measuring only customers of a year or more excludes those who churned
• No published figure states a baseline or a control group
• Your own before-and-after over one quarter is worth more than all three claims

Revenue Operations Terms Used Here

Five terms that decide whether a revenue intelligence pitch means anything to you.

Revenue intelligence

Analysing sales activity data — calls, emails, CRM records — to forecast and manage revenue, rather than relying on rep-reported status.

Pipeline inspection

Systematically examining open deals for risk signals rather than accepting the stage a rep has set.

Conversation intelligence

Recording and analysing sales calls for coaching, competitor mentions and risk. Generates its own data rather than depending on CRM hygiene.

Single-threading

A deal where the relationship runs through one contact. If they leave, the deal usually dies — which is what relationship intelligence is built to surface.

Commit

A deal a rep formally states will close this period. The gap between commit and actual is what forecasting accuracy is really measuring.