Strkr AI is not bundled on seat tiers. It is a priced, metered module a buyer opts into. The 5,000-call allowance covers typical mid-market use. Overages are predictable at a cent and change per call.
Strkr AI is an opt-in add-on module that layers AI capability onto the Strkr CRM for 49 dollars per month, with 5,000 calls included and 0.012 dollars per overage call. The module powers inbox buyer-intent scoring, email drafting, fit scoring on records, forecast risk signals, flow description polish, release-note polish, analytics narration, and SMS inbox intent routing. It is powered by a frontier AI model Strkr manages. Buyers never pick a provider or configure a model.
Six things to understand about Strkr AI: what it is, what it costs, what it does today, what is on the roadmap, how it is governed, and what it is not.
Strkr AI is a separate module a buyer enables on top of their seat plan. It is not bundled on Starter, Pro, or Scale. The buyer turns it on inside their billing surface, the module activates across the workspace, and every AI-powered surface in the product lights up for every user who has permission to see it.
The Strkr AI module is 49 dollars per month flat, which includes 5,000 Strkr AI calls per month. Overage is 0.012 dollars per call. Metering is per-call across all AI surfaces. Usage shows up in the billing admin so buyers can forecast overage before it accrues.
Eight live surfaces today. Inbox buyer-intent scoring, email drafting in the composer, fit scoring on account, contact, deal, and custom records, forecast risk signals on the forecast page, flow description polish, release-note polish, analytics narration, and the SMS inbox intent classifier.
Roadmap items include an inline AI panel on account, contact, and deal records, an AI risk chip on the deal kanban and list, and AI generate and classify blocks inside flow builder. Smart model routing (Strkr auto-selects the best model per task) is further out. None of these are live today.
Strkr AI is powered by a frontier AI model that Strkr manages. Buyers do not pick a provider, do not hold a key, do not configure a model, and do not pay the model vendor directly. The abstraction is the point. Model routing is a Strkr operational concern, not a buyer configuration surface.
Today, Strkr AI does not appear as a flow builder step (that is on the roadmap). Strkr AI does not generate call summaries (voice features are a separate roadmap). Strkr AI is not an agent framework the buyer configures. The capability is embedded in product surfaces rather than exposed as a configuration layer.
The eight live Strkr AI surfaces below are the full list of what ships in the module as of today. Everything else described in third-party coverage, blog posts, or roadmap items should be treated as upcoming rather than live.
When a new inbound email lands in the connected inbox, Strkr AI scores the sender buyer intent from 0 to 100 based on the content, the sender context, and the conversation history. Sales reps triage replies by score instead of by arrival order.
Inside the email composer, a Draft with AI button generates a reply or outreach draft based on the deal context, the contact history, and a short prompt. The rep edits and sends. The draft is a starting point, not a one-click send, because quality matters more than speed.
Account, contact, deal, and custom records get a fit score with written reasoning. The score reflects fit against the organizations ideal customer profile. The reasoning explains what drove the score so reps can act on the signal rather than guess at it.
On the forecast page, Strkr AI batches up to thirty deals and surfaces risk signals (stalled activity, declining sentiment, missing champion, approaching close date without stage progression). The sales manager sees the risk list without hunting through individual deals.
Flow builder descriptions get rewritten in plain language by Strkr AI. A complex flow becomes a one-paragraph summary that a non-admin can read and understand. The polish makes flow documentation a byproduct of building the flow rather than a separate deliverable.
Release notes written by product teams get polished by Strkr AI for clarity and tone before publication. The feature is used in the Strkr product itself and available to customer teams that want to apply the same polish to their internal release-note workflow.
On the analytics dashboards, Strkr AI narrates the biggest changes in plain English. Instead of a chart with no annotation, the dashboard carries a sentence or two explaining what moved, in which direction, and by how much. The narration is the fastest way for leaders to catch the story.
On the Strkr Messaging inbox, Strkr AI classifies inbound message intent (reply to campaign, question, opt-out, complaint, unrelated) so the queue routes to the right agent or triggers the right automation. The classification runs on every inbound message.
The roadmap items below are in active build or planning. They are not live today. Buyers evaluating Strkr AI should expect the eight live surfaces above and treat the following as directional.
An inline AI panel on the deal, contact, and account record pages where a user can ask a question in context (what are the risks on this deal, who are the stakeholders, what should I do next) and get a grounded answer from the record data. In active build.
An AI-generated risk chip on each deal card in the kanban and list views, surfacing the top risk signal without opening the deal. In active build. Different from the forecast page batch risk, which is already live.
AI generate and classify steps inside flow builder, so an automation can call Strkr AI to produce or classify text as part of a workflow. In active build. Not available today in the flow builder step library.
Smart model routing where Strkr auto-picks the right model per task behind the scenes. The buyer never configures the choice. Target is future, not near-term. The capability complements the existing managed-model abstraction rather than replacing it.
The Strkr AI module is designed to be predictable. The 49 dollar flat includes 5,000 Strkr AI calls per month, and overage is 0.012 dollars per call. The math below is the honest estimate for typical team sizes.
Five reps running typical pipeline (fifty active deals total, routine inbox volume) consume around 1,500 to 2,500 Strkr AI calls per month across all surfaces. Well under the 5,000-call allowance. The flat 49 covers the full workspace with margin.
Fifteen reps across typical pipeline, inbox, and forecast cadence consume 4,000 to 6,000 Strkr AI calls per month. Occasional light overage of 10 to 20 dollars per month on heavy months. Still predictable and the overage shows up in the billing surface before it accrues.
Fifty reps running a full go-to-market motion typically consume 15,000 to 25,000 Strkr AI calls per month. The overage lands between 120 and 240 dollars per month, which is still a small line item relative to the headcount cost. Buyers plan for it rather than discover it.
Every Strkr AI call is logged with timestamp, surface, and user. The billing admin shows usage against allowance in real time. Operations teams can see which surface is consuming calls and segment the workspace by team if the usage pattern warrants it.
Paid plans ship with a 14-day trial. The Strkr AI module is enabled during the trial so the full capability shows up during evaluation. Buyers can see every live surface against their own data before any invoice runs.
The total AI-enabled cost for a buyer is seat tier (Starter 29, Pro 59, Scale 119 per user per month) plus the Strkr AI module (49 per month flat plus any overage). Published numbers, no surprises, no hidden implementation line, no mandatory professional services.
The Strkr AI module is enabled during the 14-day trial on paid plans. See the eight live surfaces (inbox score, email draft, fit score, forecast risk, flow polish, release polish, analytics narration, SMS intent) with your real data before any invoice.
Strkr AI is 49 dollars per month flat, which includes 5,000 Strkr AI calls per month. Overage is 0.012 dollars per call. The module is not bundled on seat tiers. A buyer enables it in the billing admin, pays the flat module fee plus any overage, and the capability activates across the workspace.
Strkr AI handles that for you, picking a frontier AI model and routing calls to it on your behalf. Buyers do not pick a provider, hold an API key, or configure a model. The abstraction is deliberate: model choice is a Strkr operational concern, not a buyer configuration surface.
Eight live surfaces: inbox buyer-intent scoring, email drafting in the composer, fit scoring on account, contact, deal, and custom records, forecast risk signals on up to thirty deals at once, flow description polish, release-note polish, analytics narration, and SMS inbox intent classification.
No. Strkr AI is an opt-in add-on module. It is not bundled on Starter, Pro, or Scale seat tiers. The buyer enables it separately for a flat 49 dollars per month plus any overage. The 14-day trial on paid plans does enable the module during evaluation so buyers can see the capability before purchase.
The Strkr AI email draft feature inside the composer generates a draft that a human reviews and sends. There is no autosend. The decision to put the human in the loop is deliberate: email quality compounds over time and automated send-without-review damages sender reputation and buyer trust.
Not today. AI generate and classify steps inside flow builder are on the roadmap. Today, Strkr AI shows up in the surfaces listed on this page (inbox, composer, record fit score, forecast page, flow description polish, release-note polish, analytics narration, SMS intent). The flow builder AI nodes are an upcoming expansion.
No. Voice, dialer, click-to-call, and AI call summary features are a separate roadmap, not a Strkr AI feature today. The Strkr AI module as live today operates on text surfaces (inbox, email, records, forecast, flows, analytics, SMS). Voice is a different capability track.
Strkr AI calls run through managed infrastructure configured for commercial use. Customer data is not used to train the underlying model. Full details are in the data processing addendum, available under NDA for buyers evaluating the platform.
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