Too many places to look
Sales, finance, operations, and customer data each live in their own system and their own report.
MantisPulse is an AI-native intelligence platform built by Mantis Growth Labs. It sits above the systems you already run, is configured around your metrics and definitions, and gives leadership teams answers, early warnings, and evidence-backed recommendations.
Deployed today with a multi-location restaurant group.
Sales, finance, operations, and customer data each live in their own system and their own report.
By the time someone asks why a number moved, the moment to act has often passed.
Connecting signals across the business takes sustained attention that most teams cannot spare.
MantisPulse does that work continuously, in the language of your business.
Most tools stop at answering the question you thought to ask. Discover and Recommend are what set MantisPulse apart: it brings forward what changed before anyone asks, and suggests what to do about it, with the evidence attached.
Ask the way you would ask a sharp analyst. MantisPulse answers from your data, follows the business rules your team already uses, and shows the supporting data behind each answer.
“Why were same-store sales down at our north-side locations last week?”
Order count was flat. The drop came from a lower average ticket at two of the three locations, driven by a shift toward lower-priced items. Supporting data: item sales by location, last 8 weeks.
“Why is ARR growth slowing despite strong new customer acquisition?”
New business is on plan. The slowdown comes from churn among mid-market accounts, which has risen for two quarters and now offsets most of the new bookings. Supporting data: ARR movements by segment, last 4 quarters.
Between meetings, MantisPulse checks the business for what has changed and what it means, and a weekly brief pulls it together, so your team starts with what matters instead of hunting for it.
Ticket times at Location 12 are up 40% on its usual Friday, and three recent reviews mention slow service. Sales have held so far, so the weekly sales report does not show it.
Expansion revenue is rising, but churn among accounts in their first two years is rising faster and offsetting the gains. Total ARR still looks healthy, so the monthly revenue report does not show it.
Each recommendation comes with the signals behind it, a suggested owner, and a confidence level, so leaders can weigh it and push back. MantisPulse does not act on its own. People decide and act.
Review kitchen staffing and prep at Location 12 before the weekend. Signals: ticket times, review themes. Suggested owner: Operations. Confidence: medium.
Prioritize retention outreach to high-value customers whose product usage has declined for three straight weeks. Signals: usage trend, support tickets, renewal dates. Suggested owner: Customer Success. Confidence: medium.
Examples are illustrative and do not use customer data. MantisPulse is deployed today with a restaurant group; the B2B SaaS examples show how the same approach would apply, not a current deployment.
MantisPulse reads the data that bears on the decision, such as point-of-sale and loyalty data, through your data warehouse with read-only access. If your data is not yet in one place, we scope that first.
We set up your metrics, definitions, and business rules, such as what counts as a sale, so answers match the numbers your leadership team already recognizes.
Leaders ask questions, review daily signals and a weekly brief on what changed, and weigh recommendations in the meetings they already hold.
MantisPulse combines a consistent intelligence approach with business-specific implementation.
MantisPulse is deployed today with a multi-location restaurant group. Each new implementation is tailored to the customer’s business, data, and decisions.
Example questions are illustrative.
Agree on the decision, check the data, and define what success looks like.
Implement MantisPulse for one decision area, measured against those criteria.
Operate, refine, and expand as the value is demonstrated.
Have a recurring decision worth examining?
Start with one decision →No. MantisPulse works above them. In our current deployment it reads from the client’s existing data warehouse with read-only access. If your data is not yet in one place, we scope that in the Decision Diagnostic.
Dashboards wait for someone to look. Chat tools wait for someone to ask. MantisPulse also checks the business for what changed, explains it using your definitions, and recommends where to act.
No. It recommends, with the evidence behind each recommendation. People decide and act.
Answers follow your agreed business rules and show the supporting data behind them, so your team can check them. During the pilot we test answers against numbers your team already trusts.
It depends on the decision and how quickly we can access the data. We scope it in the Decision Diagnostic and agree on timing and success criteria before work begins.
Only the data the decision requires, agreed in writing during the Diagnostic. In our current deployment, MantisPulse reads from the client’s warehouse with read-only access, and role-based permissions limit each person to what they should see, such as a store manager seeing only their own locations. Hosting, AI providers, and data retention are agreed for each engagement.
MantisPulse is an AI-native intelligence platform delivered as a service. We implement it for your business, run it with you, and expand it as the value is proven. There is no self-serve sign-up.
MantisPulse is deployed today with a multi-location restaurant group, and we are prioritizing multi-location operators. It is designed for data-rich businesses more broadly, and we are glad to talk about others.
It depends on scope. We agree on pricing after the Decision Diagnostic, once we understand the decision, the data, and the value at stake.
Tell us about a decision your team makes every week or month and wishes it made better. We will tell you honestly whether it calls for MantisPulse, better data, or neither. Operator to operator.