Stocci provides an integrated data and AI platform that helps enterprises move from isolated AI experiments to production-ready solutions with governance and scale. The platform combines data management, low-code pipeline orchestration, generative and predictive AI modules, and MLOps capabilities in a unified environment. It emphasizes data products—reusable, governed datasets—as the foundation for scalable AI adoption.
Funding
Funding not disclosed
Founders
Product
Problem
Many enterprises invest in artificial intelligence but struggle to move beyond isolated experiments into production-ready solutions. Fragmented tools, siloed data, and a lack of governance prevent AI initiatives from scaling and delivering measurable business impact.
Solution
Stocci provides a complete data and AI platform that enables enterprises to activate AI with security, speed, and real results. The platform consolidates the entire AI lifecycle—from data ingestion and transformation to model deployment and monitoring—into a single, governed environment. It includes low-code visual interfaces that allow hybrid teams to build and manage data pipelines without heavy IT dependency, while generative and predictive AI modules connect models to internal company data for accurate, contextual responses. Stocci also emphasizes the creation of data products: structured, governed, reusable datasets that serve as the foundation for scalable AI adoption across multiple use cases.
Target Audience
Primary customers are enterprises across various sectors that need to scale AI adoption with governance, including data teams, business analysts, and IT leaders seeking to transform raw data into reusable strategic assets.
Features
- Integrated modules for data ingestion, transformation, and activation with end-to-end governance and traceability
- Low-code visual environment for creating, versioning, and reusing data products across different business areas
- Generative AI capabilities with RAG (Retrieval Augmented Generation) to connect LLMs to internal company data
- MLOps discipline ensuring versioning, monitoring, retraining, and continuous deployment of AI models
- Native integration with existing systems such as ERPs, CRMs, and CDPs
- Security and compliance controls aligned with LGPD and GDPR regulations, including access control and auditability