Enterprise AI · AI for sales

AI for enterprise sales.

A pipeline you can trust, forecasts that get checked against what closes, and sellers back to selling, built on every system that knows your customer.

Talk to us Why sales forecasts miss

Updated November 2026

An engraving of a merchant house counting room: a map held flat by brass weights on a broad table, an open ledger, dividers and an inkstand, a shelf of ledgers, a globe, and through two sash windows a harbor of sailing ships at a stone quay.

How should a sales team use AI?

Start with the data under it. A forecast or a deal alert is only as good as the systems it reads, and in most companies the deal, the contract, the support history and the product usage live apart. We join them first, then build AI that keeps the pipeline honest, checks every forecast against what really closes, and gives sellers their time back.

Pipeline you can trustEvery deal checked against what the customer is really doing.
Forecasts that get checkedScored at quarter end, so each one gets better.
The whole customerCRM, billing, support and usage on one page.
Time back for sellingThe notes, updates and prep done for the seller.

Why sales needs this now

From our research, why sales forecasts miss and connect the systems before the AI.

7%of sales teams reach 90% forecast accuracy or better, by Gartner’s count.
27%of a company’s applications are connected, on average, in MuleSoft’s survey of IT leaders.
40%of a seller’s week goes to selling, in Salesforce’s 2026 State of Sales.
51%of sales leaders using AI say disconnected systems slow it, in the same report.

Use cases

What we would build, in the order most teams need it, each on your own CRM and the systems around it. Read more on forecasting, pipeline clarity and the whole customer.

Pipeline clarity

Knowing what in the pipeline is real.

Deal riskDeals gone quiet, single threaded, or with a support case open, flagged with the reason.
Activity into the CRMCalls and emails landed as CRM records, and field updates suggested for the rep to confirm.
The weekly reviewEach rep’s deals: what moved, what slipped and what is stuck, before the meeting.
Clean recordsDuplicates, missing fields and stale close dates found and fixed with a yes.

Forecasting

A number you can stand behind.

A forecast from the recordBuilt from deals, history and usage, set beside the team’s own call.
Calls on the recordEvery override kept, so the quarter shows whose call was closer.
Scored at quarter endEach forecast checked against what closed, and kept only where it improves.
Why it movedThe change since last week, explained in plain words with the deals behind it.

The whole customer

One view across every system.

Account briefsCRM, billing, support and usage on one page before a call.
Renewal riskFalling usage and open escalations flagged months ahead of the renewal.
ExpansionAccounts using what they have and hitting its limits.
TerritoriesCoverage and capacity planned on real opportunity, not last year’s map.

Seller time

The work around the selling.

Call prepWhat the customer bought, used and asked about, before every call.
Follow upsDrafted from the call, in your voice, for the seller to send.
ProposalsFirst drafts from your own approved content and pricing rules.
CRM updatesNext steps and stages drafted from the call, so the record stays current.

Built on Business Super Intelligence

AI for sales is the first use most companies build on BSI, our intelligence layer. The same joined systems and defined numbers then answer finance, customer success and operations too.

Security

It works inside your rules.

It reads your CRM and the systems around it with the access your people already have. How we handle your data

Your CRM’s permissionsEach rep sees only the accounts and deals they can already see.
A person sendsNothing reaches a customer, and no record changes, without the seller’s yes.
Numbers from recordsForecasts and figures are computed from your data, never written by a model.
On the recordEvery suggestion and every change is kept, with who approved it.

How it starts

One use first, proven against real deals before the next.

01A working callYour CRM, the systems around it, and where the forecast and the pipeline let you down.
02Join the systemsThe CRM keyed to billing, support and usage, with pipeline and bookings defined once.
03One use firstUsually deal risk or the forecast, run beside your team and checked against what closes.
04Then the nextEach use added once the last one has earned its place.

Each use case in depth

What we build for each, how it runs, and how it starts.

Where to go next

Questions

Which CRM do you work with?

The one you run. Salesforce, Microsoft Dynamics 365 and HubSpot each have their own way in, and we work through it, with the permissions your people already have.

Will reps have to enter more data?

Less. Calls, emails and meetings become CRM records on their own, and field updates are drafted for the rep to confirm with one click.

We already have AI in our CRM. Does this replace it?

No. The AI in your CRM reads your CRM. We join it to billing, support and usage, so it, and anything we build, sees the whole customer.

How do we know the forecast is better?

Every forecast is scored against what closed, beside the team’s own call. A change is kept only when it scores better, and you see the record.

What does it cost?

It depends on how many systems and teams, and how much of the work your own people do. We say it in writing after the first call.

Tell us what you need to know. We’ll build what answers it.

Talk to us