Turn your data platform into an AI product engine.
CortexStack adds a unified AI & LLM layer on top of your existing lake or warehouse, so enterprise data teams can design, deploy, and operate AI products at scale—without rebuilding their stack.
- Works with your existing data platforms (Snowflake, Databricks, BigQuery, S3, Kafka, etc.).
- Provides a standard runtime for ML models, LLM/RAG apps, and AI automation.
- Gives you MLOps/LLMOps, governance, and impact analytics aligned with enterprise needs.
Built for the way your data team already works.
CortexStack is designed to sit on top of your data platform and empower the teams who already own data quality, governance, and analytics.
Standardize AI on top of your data stack
Give your internal customers a consistent way to consume AI from the data platform you already run.
- Standardized inference endpoints and flows instead of one-off services.
- Reuse features, data products, and pipelines across multiple AI use cases.
- Align AI workloads with existing security, lineage, and compliance.
From notebooks to governed production
A unified framework for classic ML, RAG, and LLM apps with operations baked in.
- Unified framework for classic ML, RAG, and LLM-based apps.
- Fully instrumented MLOps/LLMOps over your enterprise data.
- Faster iteration from experimentation to production services.
LLM experiences on trusted data models
Put LLMs in front of the curated metrics and dimensions you already maintain.
- Build LLM/RAG experiences that sit directly on trusted data models.
- Understand and measure AI features using standard BI tools.
- Run experiments and A/B tests tied to business KPIs.
AI as an extension of your data strategy
One AI layer over your data platform, instead of another shadow stack.
- Single AI layer on top of your data platform—no tool sprawl.
- Clear portfolio view of AI initiatives and their impact.
- Governance, policy, and auditability that passes enterprise scrutiny.
How CortexStack fits into your existing data stack.
No rip-and-replace. CortexStack layers on top of your lake or warehouse and connects to your streaming, BI, and application ecosystems.
- Data lake/warehouse (Snowflake, Databricks, BigQuery, Redshift, etc.).
- Streaming and event systems (Kafka, Kinesis, Pub/Sub).
- Data catalog and governance tools.
- CortexFlow: RAG and LLM flows over your enterprise data.
- CortexOps: MLOps/LLMOps pipelines and monitoring.
- CortexAutomate: Data-driven workflows and AI automation.
- Run them where your infra is: in your cloud account, on your VPC.
- CortexInsights plugs into your analytics stack to track AI usage and performance.
- Measure business impact per feature, product, or business unit.
- Use these insights to prioritize new AI use cases and scale what works.
3 simple packaging tiers for enterprise data teams.
These are positioning tiers for enterprise conversations. Show "Starting from …" or "Contact us" instead of hard prices depending on your sales strategy.
- Connect CortexStack to one primary data platform (e.g., Snowflake or Databricks).
- Implement 1–2 LLM/RAG or ML use cases using CortexFlow.
- Basic CortexOps setup:
- CI/CD template for model/flow deployment.
- Monitoring for latency, errors, basic usage.
- Starter CortexInsights dashboards for usage and impact on those use cases.
- Includes a Launch Sprint (4–8 weeks) with our team.
Working, production-grade AI/LLM use cases. Clear technical validation and business impact story for leadership. Foundation to expand to more teams and use cases.
- Platform-level deployment of CortexStack in your environment:
- Integration with multiple data sources (lake/warehouse + streaming).
- Role-based access and governance mapped to your IAM.
- Standardized CortexFlow and CortexOps patterns:
- Reusable templates for RAG, LLM flows, and ML pipelines.
- Enterprise-grade monitoring and alerting.
- Initial CortexAutomate workflows for key data-driven processes (e.g., alert triage, document intake to warehouse).
- Expanded CortexInsights: AI product analytics for several teams and use cases.
- Co-design program (10–16 weeks) with your core data platform & ML team.
A shared AI layer that multiple data, ML, and analytics teams can build on. Consistent patterns for shipping AI products across the enterprise. Governance and observability that satisfy security, risk, and compliance.
- Full CortexStack rollout as the standard AI fabric across multiple business units.
- Multi-region / multi-account architectures and advanced governance.
- Deep integration with:
- Your data catalog and lineage tools.
- Your ticketing, CRM, and ERP systems for automation.
- Your existing MLOps/DevOps tooling where applicable.
- Programmatic enablement:
- Playbooks and templates for internal data & AI teams building on CortexStack.
- Training tracks for platform engineers, ML engineers, and analytics teams.
- Ongoing advisory, roadmap co-planning, and architecture reviews.
- Advanced CortexInsights:
- Portfolio-level impact reporting.
- Executive dashboards and narratives for CDO/CTO/Head of Data.
A consistent AI fabric all data domains can leverage. Strong internal ecosystem of teams building on the same foundation. AI becomes an integral, governed extension of your data platform strategy.