Stackmint provides a governed AI execution platform that lets agencies and consultancies turn their best playbooks into reusable, client-deployable AI products. The platform separates intelligence from execution, enabling teams to build capabilities conversationally while enforcing permissions, approvals, budgets, and audit trails across every deployment. It includes automated revenue distribution rails with a 75% partner revenue share on each workflow execution stream.
Funding
Funding not disclosed
Founders
Product
Problem
Agencies and consultancies scale expertise by adding headcount, which caps margins and ties revenue to labor. Their best methodologies are rebuilt for each client, delivered manually, and trapped inside individual employees, preventing scalable reuse and recurring revenue.
Solution
Stackmint provides an expertise runtime that lets firms build their best playbooks once and deploy them as governed AI products across every client. Capabilities are built conversationally, then wrapped with enterprise-grade controls—permissions, approvals, human-in-the-loop checkpoints, client-isolated memory, model allow/deny lists, budget limits, and audit logs—that travel with the capability wherever it runs. The platform separates intelligence from execution, allowing teams to choose any AI model while keeping execution governed on Stackmint's runtime. Agencies can build centrally, configure independently per client, control versions and rollouts, and package proprietary execution into white-labeled software assets deployed in isolated client environments. Revenue decouples from delivery cost as the same product is deployed repeatedly with zero cloning overhead.
Target Audience
Primary customers are agencies and consultancies that package sector expertise into repeatable software assets, as well as enterprise operators (CDOs, CTOs, Chief Supply Chain Officers) who need industrialized, auditable AI execution with measurable ROI.
Features
- Conversational capability builder that converts expert methodologies into executable AI products without custom code
- Built-in governance layer with permissions, approvals, human-in-the-loop checkpoints, and per-client budget controls
- Client-isolated memory and data boundaries enforced at runtime for secure multi-tenant deployments
- Model policy engine supporting allow/deny lists to control which AI models a capability can use
- Full audit trail capturing every run for compliance and accountability
- Centralized build with independent client configuration, versioning, entitlement, and credential management
- White-label capability packaging for agencies to productize services like content factories and support tiers
- Partner Portal with automated billing rails and a 75% revenue share on every successful workflow execution stream