Programme performance reporting
Contract metrics collected and reported without spreadsheets.
- 1Pulls data from delivery systems
- 2Calculates contract metrics
- 3Produces agency-ready reports
Washington, DC · Data & AI Platforms
Data platforms and analytics for DC organisations, from programme reporting to member and policy data, built to federal security standards where needed.
Data & AI Platforms in Washington, DC
Washington runs on policy, compliance and public service: federal contractors, trade associations, law and lobbying firms, think tanks and health organisations. AI here has to meet federal security standards and hold up to public scrutiny.
Where it fits
Contract metrics collected and reported without spreadsheets.
Understand engagement and renewal risk.
Clean data for quality and cost analysis.
Built for District of Columbia rules
AI features hosted on authorised cloud services, inside the authorisation boundary.
Controlled unclassified information kept inside assessed environments, AI tools included.
Inventories, risk practices and human oversight for high-impact AI.
Safeguards and a business associate agreement for anything touching patient data.
Security safeguards and prompt notice if personal data leaks.
Working together · Eastern Time
Your morning is our evening, so we meet live at the start of your day and build while you sleep.
How we work
We map your data sources, flows, owners and quality issues.
We design a platform that fits your cloud, scale and budget.
We deliver pipelines, models and dashboards in working increments.
We set up monitoring, alerts and governance your team can run.
Yes. We design on the authorised cloud regions and services your contracts require.
Access by role, encryption, audit logs and data classification, aligned with the NIST controls behind federal security frameworks.
MLOps is the set of practices and tools for deploying, monitoring and updating machine learning models reliably, much as DevOps does for software. It keeps models accurate as data changes.
We work with the major cloud providers and with on-premise environments, and design the platform around the tools and contracts you already have.
Not always. We often build the data foundations a specific AI use case needs first, then extend the platform as more use cases follow.
Let's talk
We help you navigate Enterprise AI, from first use case to production.
Let's connect