113 Sales AI Agents, Live in Production.

Upload account health data and get the accounts showing churn signals, what each signal actually is, and which ones are an expansion opening in disguise.

Upload your customer base and get it divided into segments that emerge from the data, each with what defines it, what it is worth, and the one motion that fits it.

Answer the routine questions that reach a sales inbox from your own approved material, and route everything else to a person rather than guessing.

Work out which missing customer fields are actually worth chasing, who would know each one, and draft the request — instead of sending a blanket form.

Read a customer message for the objection underneath it — what is actually being raised, how serious it is, and the response your own material supports.

Describe the customer and get two or three bundles built for them specifically, each with what is in it, what it costs, and who inside the account it is aimed at.

Upload what happened after the proposal went out and get an honest read on intent — which signals mean something, which mean nothing, and what the silence actually tells you.

Read what a customer's behaviour says they need next, and separate a real signal from a coincidence before anyone acts on it.

Score how trustworthy each customer profile is — not just whether fields are filled, but whether what is in them is recent enough to act on.

Check that every upsell conversation left a record — what was offered, what was agreed, and who approved it — so nothing sold sits outside the audit trail.

Upload a customer usage export and get accounts ranked by expansion potential, the segments behind them, and a playbook for the top opportunities.

Route an upsell proposal to the right approver with the account's risk in view — so nobody approves an expansion into an account that is quietly in trouble.

Upload customer-facing text and get every claim that breaks your messaging policy rewritten — with the original and the replacement side by side so a reviewer can check each change.

Read what customers said after seeing a proposal — won, lost, and still open — and find what the proposal itself is getting right and wrong.

Work out which reviewers a proposal actually needs, in what order, and by when — instead of sending it to everyone and waiting.

Draft a proposal from your approved boilerplate and the deal's own facts — with a visible marker anywhere the library has nothing to say.

Track the open exceptions on a bid — the non-compliant answers, the unanswered clarifications — and establish which are genuinely closed before submission.

Upload a proposal draft and every reviewer's comments, and get one consolidated redline list with conflicts between reviewers surfaced rather than silently resolved.

Turn a signed-off proposal into the records the rest of the business needs — the CRM update, the finance handover, the delivery brief — each with only what the proposal actually establishes.

Check a proposal package before it is submitted — every required document present, every figure consistent across them, and every submission rule met.

Establish which proposal version the customer actually holds, what changed between versions, and whether the record can prove it.

Paste a customer message and get it checked against the requirements you are already working to — what changed, what is new, and what it does to scope you have already priced.

Upload an RFP or requirements document and get every requirement extracted, classified by whether you can actually answer it, with the ambiguous ones written as clarification questions.

Turn an RFP into a drafted response built from your approved answer library, with every unanswered requirement listed rather than quietly filled in.

Upload a pipeline export and get a portfolio health score, at-risk deals with root causes, stage-by-stage breakdown, and a rescue plan for everything that is slipping.

Upload closed-lost deals with their loss notes and get every loss classified by reason, the patterns across them, and what to change first.

Describe a deal heading into negotiation and get an honest readiness check — what is actually established, what is assumed, and the negotiation position the evidence supports.

Assign open deals to the rep best placed to win each one — by sector experience, prior wins, and actual capacity, with the reasoning shown so a manager can override it.

Tell a rep the single most useful thing to do next on each open deal, from what the record shows — and say plainly where the answer is to wait.

Review a set of opportunities the way an auditor would — whether each stage and forecast figure is supported by what is recorded, not by what the owner believes.

Take opportunity records that use different stage names, currencies and date formats, and harmonise them into one comparable set — without hiding what could not be mapped.

Build one audit-ready profile of an opportunity from the records scattered across systems, with every fact traced to where it came from.

Turn a messy opportunity record into a summary a stakeholder can read in a minute — the position, the numbers, and what is asked of them.

Upload open opportunities and get a win probability for each one, the drivers behind every score, and an honest list of what the data cannot tell you.

Check whether a pipeline can actually make its number — coverage, stage mix, and how much of it rests on deals that have not moved.

Find the records that do not make sense together — a plan that does not match its price, seats above what was sold, a renewal date that has already passed.

Reconcile what was sold, what is provisioned, and what is invoiced — and find the accounts where those three do not agree.

Check a renewal against what renews on standard terms, and route anything non-standard to the level that can actually approve it.

Read what customers said at renewal — those who stayed and those who left — and find what actually drove each decision rather than what was easiest to record.

Pick an account renewing soon and get a renewal proposal drafted with the uplift maths shown, the likely pushback anticipated, and your negotiation room stated plainly.

Rank the accounts renewing soon by how likely the renewal is to slip, with the evidence behind each ranking and where the owner should start.

Open a retention case for an at-risk account and get each team briefed on their part — the same facts, different asks, all held for approval before anything goes out.

Rank open retention cases by what is genuinely saveable rather than by what is largest — with the intervention each one needs and the ones honestly worth letting go.

Compare what a customer is actually using against what their contract entitles them to, and get every overage, shortfall, and unbilled entitlement listed before the renewal conversation.

Standardise messy subscription records into a consistent shape — and separate what can be normalised safely from what needs a person to decide.

Check a CRM activity note before it saves — whether it records what actually happened, whether the next step is real, and whether anything in it should not be written down.

Check a closed deal's paperwork before it hands over — which documents exist, which are missing, and what fulfilment cannot start without.

Fill a deal document from the account record, leaving a visible blank wherever the record has nothing rather than a plausible-looking guess.

Read a customer message for anything that actually moves the deal, and get the CRM update it implies drafted — with what is a milestone kept separate from what only sounds like one.

When a control flags a deal, assemble what a reviewer needs to judge it — what the rule caught, what the record explains, and what still needs asking.

Paste meeting notes and get every commitment pulled out with its owner and due date — separating what you promised the customer from what they promised you.

After an offer is approved, check that every system now says what was approved — and produce the audit record showing what was changed, by whom, and when.

Audit a batch of closed deals against your sales policy — approvals that were never recorded, discounts above authority, activity logged after the fact — with an audit note for the record.

Paste a call note or customer email and get a clean CRM activity record, the commitments made on both sides, and the follow-ups — ready for approval before anything is logged.

Turn a closed deal into a validated order payload — every field checked against the signed terms, with anything that would bounce in fulfilment caught before it is submitted.

Check that every executed agreement is archived, that the archived copy is the executed one, and that nothing is superseded without its replacement on file.

Answer an auditor's question from your contract archive, with every statement traced to the clause it came from — and an explicit list of what the archive does not answer.

Generate a contract from your own approved clause library and the agreed deal terms, then check the result for anything missing or non-standard before it leaves your hands.

Before a contract risk assessment starts, check whether the data it needs is actually there — which fields are complete, which are stale, and what cannot be assessed yet.

Upload a non-standard deal and get it checked against your approval matrix — which exceptions it contains, who has to sign off, and a routing message drafted for that approver.

Upload an agreement and get it checked against your own contracting standards — which required protections are missing, which are weaker than standard, and what to ask for.

Summarise the non-standard terms a reviewer is being asked to accept, what each one exposes, and which have precedent — so a review takes minutes rather than an afternoon.

Track a contract through negotiation rounds — what each side has moved on, what is still open, and which points have been reopened after being agreed.

Upload a customer's proposed contract terms and get every clause assessed against your negotiation position, with the risky ones quoted and a counter-ask list to take into the call.

When a lead's reply is too ambiguous to route automatically, get it summarised for a human — what they seem to want, what is unclear, and who should pick it up.

Check a lead's contact details against what can be found publicly — whether the person is still in that role, whether the details are structurally sound, and what could not be confirmed either way.

Upload a contact export and get duplicate records clustered, a merged golden record for each cluster, and an audit note explaining every merge decision.

Ask a question about the lead records in your CRM and get an answer computed from the selected rows, with the records it used shown alongside.

Upload the same customer's records from several systems and get one reconciled profile, with every conflict between sources shown rather than silently resolved.

Look at where enrichment keeps getting records wrong and propose rule changes — with what each change would have done to the records you already have.

Turn a lead's stated availability into a meeting proposal that works in both time zones, with the arithmetic shown and the invite held for approval. Nothing is sent.

Pick a lead and get a one-page brief for the call: what the record says, what to open with, what to ask, and what you still do not know.

Pick dormant leads worth another try and get a re-engagement email drafted for each one from what its record actually says. Every draft is approved individually — nothing is sent.

Upload new leads and your rep roster, and get each lead assigned to a rep by fit and current workload — with the reasoning shown so a manager can override it.

Route a single inbound lead to the right rep immediately, with the rule that decided it and a handover note the rep can act on.

Check lead records for the errors that make outreach fail — malformed contacts, impossible values, fields that contradict each other within the same record.

Upload leads with their engagement history and get the ones going cold ranked by what they are worth, with the specific decay signal behind each and who to escalate.

Sort the leads that broke a rule into the ones worth a person's time and the ones that are simply noise — and escalate only the first.

Score inbound leads against your ideal customer profile and route each one, with the reasoning shown so a rep can disagree.

Consolidate the same lead arriving from several sources into one record with a traceable history — which source said what, and which claim survived.

Compare what your lead scores predicted against what actually converted, and propose changes only where the outcomes support them.

Upload quotes flagged as pricing exceptions and get each one explained, classified, and routed — separating genuine one-offs from a pattern nobody has fixed.

Check a proposed price against your pricing policy — margin floors, discount authority, and the rules that apply to this customer's sector — before it is quoted.

Describe a deal and get three defensible pricing scenarios compared side by side, with the margin maths, the risks in each, and a recommendation.

Describe what the customer wants and get a priced quote built from your own price book and discount policy, validated against that policy before it leaves your hands.

Compare what was signed against what was approved and get every difference found — line by line, with the ones that change the money separated from the ones that do not.

Check a quote request for everything needed to price it, and get the questions that close the gaps drafted for the requester.

Paste an inbound quote request and get a go/no-go decision against your qualification rules, with what is missing listed and a reply drafted either way.

Find quotes whose status disagrees across CRM, e-signature, and finance — the signed-but-unbilled, the expired-but-open, the billed-but-unsigned.

Pick a lead, say what you are offering, and get an outreach email written from what the record actually says — with every assumption it had to make listed. Nothing is sent.

Queue a batch of outreach at send times that respect each recipient's time zone and working hours — with the pacing rules that stop a batch reading as a blast.

Pick a lead and get a multi-touch sequence planned across channels — each touch with its timing, its angle, and the exit condition that stops it.

Check a prospecting list for records you are not entitled to contact — no lawful basis recorded, an opt-out ignored, or a source that cannot be evidenced.

Score a raw prospect list against your ICP, group it into workable segments, and mark clearly which scores rest on evidence and which on inference.

Turn agreed requirements into acceptance tests the customer would sign off — each traceable to a requirement, prioritised, with the untestable ones named.

Take rough requirements from a discovery call and turn them into ones an engineer could build against — with everything still ambiguous written as a question rather than resolved by guessing.

Describe what the customer needs and get a solution architecture written against your own standards, with every component justified and every deviation from standard called out.

Score which solution components actually fit a customer's requirements, by feasibility rather than by what would be nice to sell.

Paste discovery notes and get them turned into user stories with acceptance criteria — and an explicit list of what the notes do not say clearly enough to write.

Upload your won and lost deals and get an ideal customer profile derived from what actually closed — with the qualifying signals, the anti-patterns, and how much the data can really support.

Ask a market question and get a synthesis grounded in live search results and your own research library, with every claim traceable to a source and the gaps named.

Name a broad market and get it cut into workable segments, ranked by what your own won deals suggest and what public sources support — with the sizing arithmetic shown.

Check whether you can actually deliver an opportunity before you chase it — against your own capacity, skills, and current commitments, not against how attractive it looks.

Upload leads with what became of them and get your qualification criteria tested against outcomes — which ones predict conversion, which ones cost you good leads, and what to change.

Check an account plan against what a plan is supposed to contain — whether its actions have owners, whether its targets are grounded, and whether it says anything the data does not support.

Name an account and get external signals searched for anything that changes your plan — funding, restructures, leadership moves, regulatory news — with what is corroborated separated from what is rumour.

Turn an approved territory or account plan into assigned tasks — each with an owner, a date, and what it depends on — and hold the assignment messages for approval.

Upload your account list and get territories balanced by potential rather than headcount, with each account assigned, the workload compared, and a plan document to circulate.

Scan territories for the problems that only show at territory level — coverage that has thinned, value concentrated in one account, a rep carrying more than the numbers suggest.

Check customer-facing material against what you are actually permitted to say in a regulated sector — certifications, regulatory language, and claims that need a caveat.

Describe the prospect and the conversation ahead, and get the right assets from your own collateral library — plus an honest list of what you do not have.

Upload won and lost deals and get close rates cut by segment, source, and stage — with the patterns that actually explain the differences rather than restating them.

Upload a sales performance export and get quota attainment, rep and territory breakdowns, risk flags, and coaching recommendations for anyone falling behind target.