Trusted Data
Operations For
The AI Era

Clear Fracture builds AI-native systems that help complex organizations discover, govern, engineer, and operate all the data their missions depend on. Our flagship platform, Belvedere, turns data needs into deterministic, auditable workflows across the stack you already run.

Data Engineers & Stewards
Belvedere
BelvedereAgentic Data Manager
Knowledge
Workflow
Observability
Data SourcesS3, APIs, Oracle, SAP
PlatformsSnowflake, Airflow, dbt
LLM ModelsClaude, OpenAI, Llama
ConsumersDashboards, Apps, Analysts
Analytics, Executives, Data Scientists

Trusted By

Department of War
Intelligence Community
Carahsoft
Unfiltered Media Group
TapHere! Technology
Amazon Web Services

Complex Organizations Need Trusted Data Operations That Can Keep Pace With AI

Unify the Stack You Already Have

Agents operate across the systems you already run, so complexity drops without a rip-and-replace program.

Preserve Meaning Across Every Layer

Definitions, context, and business rules stay intact through every transformation instead of getting lost in pipeline code.

Make Every Output Provable

Deterministic, auditable, repeatable outputs make AI-generated data products something your teams can actually trust.

Source systems multiply. Definitions drift. Tribal knowledge disappears. Pipelines break quietly. Every new AI initiative raises the stakes because bad context now moves faster than ever.

AI agents change the equation, but only when they produce deterministic, auditable, repeatable output that carries context through every transformation layer. No hallucinations. No black boxes. Clear Fracture harnesses agentic AI to automate the engineering while preserving the meaning that makes the output trustworthy.

Belvedere

Meet Belvedere™, Your Agentic Data Manager

Belvedere is Clear Fracture's flagship platform for trusted data operations. Declare what data you need. Belvedere handles everything behind it: discovery, governance, pipeline generation, observability, and repair across your existing stack.

app.clearfracture.ai/pipelines/logistics-monitoring
Live
Global Logistics MonitoringUnsaved
Source

Carrier Tracking Systems

Source

Warehouse Management Suite

Source

Customs & Compliance Feeds

Transform

Normalize carrier schemas

Reconcile tracking formats across all carrier platforms into a unified shipment event model with standardized status codes.

Transform

Correlate shipment lifecycle

Link tracking events to warehouse records, building end-to-end shipment timelines with handoff traceability.

Transform

Validate compliance holds

Cross-reference customs declarations against regulatory rules, flagging holds and tariff exceptions in real time.

Transform

Publish to operations layer

Merge correlated and validated streams into a single governed dataset for the global operations dashboard.

Transform

Score delivery risk

Apply ML-driven risk scoring on the published dataset using carrier history, weather, and route congestion signals.

8 nodesDataUnsaved changes
Belvedere AIOnline

How does the risk scoring work?

The pipeline analyzes historical delivery patterns, current weather, and real-time route congestion across all carriers. Each shipment gets a risk score from 0–100, with alerts triggered above 75.

Ask about this pipeline
Every Source DiscoveredEvery Pipeline GovernedEvery Change MonitoredEvery Output Auditable

Define The Outcome. Belvedere Handles The Data Operations Behind It.

Belvedere turns intent into governed, production-ready data operations: discovery, contracts, pipelines, observability, and repair. No scripting, no manual plumbing, no vendor-specific lock-in.

Knowledge Arm: Learns Your Landscape

Know where every piece of data lives, what it means, and how different teams define it automatically. Business context persists even when people leave.

Workflow Arm: Acts with Precision

Go from data need to production pipeline in minutes, fully tested, auditable, and running on your existing infrastructure.

Observability Arm: Monitors and Self-Heals

Real-time monitoring catches schema drift, definition divergence, and quality anomalies before they compound downstream. Belvedere diagnoses and repairs before you notice.

From scattered data to confident decisions

Your data is everywhere. Your team needs it in one place, clean and ready. Here's how Belvedere makes that happen.

Step 01

Discover and connect everything you have

Scattered data across dozens of systems? Belvedere’s Knowledge Arm discovers where your data exists across CRMs, ERPs, file shares, and APIs, then catalogs the full landscape automatically. It knows what you have before you do.

Sources mapped • systems connected • landscape visible

Step 02

Understand what you’re working with

Before anything moves, Belvedere builds a living knowledge base that captures what every field means, who owns the definition, and how it relates to the rest of your data. When “revenue” means different things to different teams, both definitions are captured and made explicit, so context persists even as people rotate.

Living knowledge base • definitions captured • context preserved

Step 03

Turn messy into trustworthy

Inconsistent formats, duplicate records, missing values: the stuff that makes analysts distrust their own reports. Belvedere’s Workflow Arm configures deterministic, auditable transformation rules that enforce contracts between data producers and consumers with transparent, repeatable results every time, deployed to whatever platform you choose.

Deterministic • auditable • ready to analyze

Step 04

Deploy anywhere without lock-in

Belvedere sits above your execution platforms as the configuration plane. Pipeline logic is portable, transparent code that deploys to Snowflake, Databricks, Airflow, or anywhere else. Switch platforms without recoding.

Consume from any source • deploy to any platform • zero lock-in

Step 05

Ready for decisions and ready to scale

Your pipelines deliver clean, structured, queryable data with the context that makes it trustworthy for your analysts, dashboards, ML models, and AI agents. As your data grows, Belvedere’s configuration plane scales with compute, not manpower.

Structured • queryable • ready to scale

Insights from ClearFracture

Turn GitHub Repositories Into Explorable SysML v2 System Models

Turn GitHub Repositories Into Explorable SysML v2 System Models

Jeremy Fields and John Sutton6 min readSystem ModelingPublished August 5, 2026

SysML Repo Modeler is now open source and free to use. It turns one GitHub repository—or many—into an explorable SysML v2 system model. Get the code on GitHub.

It gives us a coherent way to visualize our own repositories, services, APIs, and layers of institutional knowledge in an exploratory systems view. And now it’s open source for anyone to freely use.

Explore a Live Model

Want to see the result before getting into the details? Start with the live Supabase Platform model, which maps five repositories and four languages as one system. You can also explore the OpenClaw model, the n8n model and the Ollama model. All four sit side by side in the SysML Repo Modeler gallery, with the repository, part and connection counts for each.

The SysML Repo Modeler model of Supabase Platform showing services and dependencies across five repositories

Open the live Supabase Platform model — click the image to search, filter, and explore the system.

The Problem: Architecture Lives in Too Many Places

The reality is that modern systems are scattered across multiple repositories, services, APIs, and layers of institutional knowledge. The challenge is not that teams lack documentation; it is that documentation struggles to keep up with what the code does.

Traditional Model-Based Systems Engineering (MBSE) documentation can be useful, but it is often manually maintained across disparate software platforms that require significant user knowledge and training, with limited ability to transfer data between tools. As a system evolves, the diagram becomes a snapshot of what people thought a system looked like but not necessarily what exists now.

Agentic Data Engineering: When AI Agents Build Trusted Production Pipelines | Webinar

Agentic Data Engineering: When AI Agents Build Trusted Production Pipelines | Webinar

Brian FrutcheyBrian Frutchey1 min readData EngineeringPublished August 1, 2026

During this live webinar we learned how appropriately designed agentic data engineering changes the equation. We also discussed autonomous AI agents can design, build, validate and govern production-grade data pipelines while keeping every decision auditable, every transformation explainable and every cost dramatically lower than AI or manual approaches.

What was covered during this webinar:

  • Why chatbot-style AI fails at scale for mission-critical data work

  • How Belvedere is a force multiplier for your existing data engineers and IT investments

  • Real-world metrics: 5-10x effort and time reduction in pipeline development

  • How to maintain IC-compliant auditability, human oversight and policy enforcement while accelerating delivery

  • Live demonstration of an agent building and deploying a trusted intelligence data pipeline from raw sources to governed outputs in minutes

Clear Fracture’s Belvedere™ Assessed “Awardable” for Department of War work in the CDAO’s Tradewinds Solutions Marketplace

Clear Fracture’s Belvedere™ Assessed “Awardable” for Department of War work in the CDAO’s Tradewinds Solutions Marketplace

2 min readPress ReleasePublished July 27, 2026

FOR IMMEDIATE RELEASE

Vienna, VA — July 27, 2026 — Clear Fracture LLC, developer of Belvedere™, the Agentic Data Manager, today announced that it has achieved “Awardable” status through the Chief Digital and Artificial Intelligence Office’s (CDAO) Tradewinds Solutions Marketplace.

The Tradewinds Solutions Marketplace is the premier offering of Tradewinds, the Department of War’s (DoW’s) suite of tools and services designed to accelerate the procurement and adoption of Artificial Intelligence (AI)/Machine Learning (ML), data, and analytics capabilities.

Belvedere puts AI agents to work as data engineers. Analysts and mission owners describe what they need in plain language; Belvedere’s agents discover the source data, design the transformations, and compile them into governed, production-ready pipelines that run on the organization’s existing infrastructure. The agents build the pipeline; they are not the pipeline. Every pipeline they produce is transparent, auditable, and repeatable, and it runs as ordinary code, keeping operations cost-efficient at mission scale.

“Mission teams lose too much time wiring data together by hand, and the systems that result are hard to trust and hard to maintain,” said Brian Frutchey, Chief Technology Officer of Clear Fracture. “Belvedere’s agents do that engineering work in the open. Every pipeline they build can be inspected, audited, and run again tomorrow. Awardable status through Tradewinds gives DoW customers a direct path to put that capability on contract.”