AI & Analytics

AI that draws on the records you already trust. Grounded AI, API-led integration, and analytics for government.

91%

of public sector IT leaders say data integration is a major obstacle to adopting AI.

The model is rarely the hard part. Connecting it safely to trusted data is. That is the problem Iron Brick solves.

Source: MuleSoft Connectivity Benchmark Report, public sector findings, 2025

What We Deliver

We connect AI and analytics to the systems of record your agency already trusts, so every answer traces back to authoritative data.

AI Readiness & Data Roadmap

We assess your data, systems, and governance against the AI outcomes you want, then deliver a phased roadmap with architecture choices, risks, and cost.

AI Grounded in Systems of Record

Retrieval and agent tools built on governed APIs and the Model Context Protocol, so AI answers carry citations and respect each user's access rights.

API-Led & Event-Driven Integration

MuleSoft integration networks that unlock legacy and cloud systems once and reuse them for applications, analytics, and AI.

Analytics & Data Quality

Databricks pipelines, data quality rules, and lineage that give program leaders dashboards and models they can trust.

AI Operations & Enablement

Monitoring for accuracy, cost, and security in production, plus runbooks and a Center for Enablement so your team can own the platform.

Secure AI & Governance

Data classification, masking of sensitive fields, least-privilege access, and audit trails that feed your SOC and SIEM.

Reference Architecture

AI never reaches into a database directly. It calls governed APIs, and every call is authorized, logged, and attributable.

SYSTEMS OF RECORDAPI-LED INTEGRATIONAI ACCESSAI AND ANALYTICS Case managementFinancial systemsGrants and benefitsData lake · Databricks Experience APIsper app, per channelProcess APIsbusiness rules, joinsSystem APIsone per system of record MCP gateway tools = governed APIsper-user authorizationrate and scope limits Models and agents answers with citationshuman review where required Analytics dashboards and modelson the same governed data Across every layer: identity and least-privilege access · audit logging · SIEM monitoring · data classification (PII)
System, process, and experience APIs follow MuleSoft's API-led connectivity pattern. The same governed APIs serve applications, analytics, and AI.

Example Use Cases

Illustrative patterns we design for in government. Each one depends on reliable access to authoritative records.

Case Summaries with Citations

Caseworkers get a summary of a case file where every statement links to the underlying record, cutting review time without losing accountability.

Eligibility Checks Against the Source

AI assists eligibility reviews by querying authoritative systems through APIs rather than relying on copied or stale data.

Program and Spend Analytics

Leaders ask questions in plain language and get answers computed from the financial system of record, with the query shown.

Security Alert Triage Support

Analysts get AI-assisted context on alerts drawn from SIEM, endpoint, and asset data, while decisions stay with the analyst.

Ways to Engage

Start small, prove it, then scale.

Assess

A readiness assessment that maps one mission question to the systems of record that answer it, and identifies data, security, and governance gaps.

Prove

A pilot or proof of concept that builds one grounded AI or analytics use case on governed APIs, with measured accuracy and a security review.

Scale

Production delivery that hardens, extends, and operates the platform across programs, with enablement for agency staff.

Why We Build on MCP

Quick answers about the Model Context Protocol.

MCP is an open standard for connecting AI assistants and agents to data sources and tools. Instead of a custom integration for every model and every system, one MCP server exposes a capability that any MCP-compatible AI can use.

It lets AI work with current, authoritative data instead of a stale copy, and it gives you one controlled place to decide which data and actions each AI tool can reach.

MCP itself is a protocol. Security comes from how it is deployed. We place MCP in front of governed APIs, enforce per-user authorization, limit scope, and log every call to your monitoring tools.

No. We work with the integration platforms you already have. MuleSoft is a strong fit when you need to unlock many legacy systems in a reusable way.

Start with one mission question

In a one-hour briefing we map where its answer lives today and what it takes to ground AI in that data.

Schedule a Briefing