Requests are routed through cloud-native AI services — AWS Bedrock, Azure OpenAI Service, and Google Cloud Vertex AI — so organizations can leverage the governance frameworks of the major cloud providers. With token-level access controls, IT leaders can govern who uses LLMs, how they are used, and how many tokens are consumed — eliminating manual API key sharing, preventing uncontrolled spend, and ensuring enterprise intellectual property stays secure.
“Our clients want the speed of LLM adoption without sacrificing governance or security,” said Brian Carter, Delivery Manager at ProCogia. “Data Science in a Box puts IT in control of LLM use through token-level policies, while giving developers seamless access to the tools they need.”
Key Features & Benefits
- Multi-cloud ready – Deployable on AWS, Azure, or Google Cloud
- Flexible integration – Works with or without Posit Workbench
- Cloud-native governance – Built on security models from AWS, Microsoft, and Google
- Token-level control – IT governs usage by user, team, and project
- No shared API keys – Access provisioned via enterprise SSO and IAM
- Auditable and compliant – Centralized logging, guardrails, and evaluation workflows
- Grounded AI – Knowledge bases enrich responses with enterprise content
Industry Use Case: Pharma SAS-to-R Migration
In life sciences, ProCogia is applying Data Science in a Box to accelerate SAS-to-R migration. By embedding CDISC standards, pharmaverse guidance, and paired SAS–R code examples into knowledge bases and knowledge graphs, statistical programmers can query mappings and validation steps directly in their IDE. This reduces timelines while maintaining governance and traceability.
Turnkey Deployment
The Data Science in a Box service includes:
- Environment assessment and architecture review
- Secure SSO integration with AWS, Azure, or Google AI services
- Toolkit configuration with enterprise defaults
- Custom knowledge base connectors from Salesforce, SharePoint, code repositories, and more
- Guardrails for PII handling, logging, and compliance
- Enablement sessions for administrators and developers
Deployments can be completed in as little as one week, with phased rollouts available for more complex environments.
“For companies that can’t risk exposing their intellectual property to the public, generative AI has felt out of reach,” said Bill Carney, CEO of ProCogia. “Data Science in a Box changes that. While traditional deployments demand hundreds of IT staff and months of effort, we make it secure, governed, and enterprise-ready—in as little as a week. It’s not just a toolkit—it’s the blueprint for the future of AI: safe, scalable, and instantly operational.”
Resources
About ProCogia
ProCogia is a data and AI consultancy headquartered in the Pacific Northwest. We help enterprises transform complex data into actionable intelligence, specializing in life sciences, telecom, and financial services. By combining cloud-native infrastructure with data science expertise, ProCogia empowers clients to accelerate AI adoption, improve decision-making, and unlock innovation.
Media Contact
Rose Vermazen, ProCogia, 1 508-685-8545, [email protected], https://procogia.com/
SOURCE ProCogia
