BelvedereMeet Belvedere:

Your Agentic Data Manager

Declare what data you need. Belvedere handles everything behind it: discovery, governance, pipeline generation, observability, and repair across your existing stack, with deterministic results your teams can verify and trust.

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Declarative data ops

You define the goal. Belvedere engineers the solution.

Describe the data products you need in plain, goal-oriented terms. Belvedere's agents harness AI speed and intelligence to derive contracts, reason through system models, and generate deterministic, repeatable implementations you can verify and trust — delivering in minutes, not the weeks or months you're used to waiting.

  • Plain-language in, deterministic code out — no hallucinations
  • Every output is verifiable, repeatable, and auditable
  • AI speed without sacrificing trust or control
  • Minutes to production, not weeks
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

Score delivery risk

Apply ML-driven risk scoring based on historical carrier performance, weather, and route congestion signals.

6 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
app.clearfracture.ai/catalog
Live
BelvedereData Catalog
SIGINT Feed AlphaDatabase Connection
14 fields
Classification & Security
MarkingTS/SCI — Top Secret / Sensitive CompartmentedTS/SCI
DisseminationNOFORN — Not Releasable to Foreign NationalsNOFORN
Handling CaveatSpecial handling procedures apply
Access & Releasability
ReleasabilityREL TO USA ONLYUSA Only
Data OwnerSIGINT Operations Division
Access LevelAuthorized personnel — need-to-know
Topic Taxonomy
DomainSignals Intelligence / CommunicationsInferred
Content Fieldsintercept_body, metadata_header
ClassificationLLM topic classification availableAI
Source Metadata
CategoryDatabase Connection
Update Freq.Real-time / Event-driven
Quality Score92 / 100 — High confidence
Data Governance
RetentionMission-defined retention policy
PII DetectionScanned — 3 fields flaggedScanned
LineageCollector → Catalog → EnrichmentTracked
Inferred Schema
14 fields
Tintercept_idUUID
Ttimestamp_utcTIMESTAMP
Tsource_platformVARCHAR
Tintercept_bodyTEXT
Data Catalog

Agentic discovery across your entire data landscape.

Belvedere's Knowledge Arm automatically discovers, classifies, and catalogs every data source across your environment — from cloud storage and databases to streaming feeds and legacy systems.

Each source is enriched with classification markings, access controls, topic taxonomy, governance policies, and inferred schema — capturing not just structure but what the data means, all without manual intervention.

  • Finds every source — cloud, on-prem, or air-gapped
  • Schema, classification, and governance inferred automatically
  • End-to-end lineage from ingestion to delivery
  • PII detection and releasability controls built in
Observability & Self-Healing

Drift happens. Belvedere handles it.

Belvedere's Observability Arm monitors every pipeline and integration point in real time. When something drifts — a schema change, a quality anomaly, a broken contract — it detects the issue and diagnoses root cause automatically. High-confidence fixes are applied instantly. Lower-confidence changes are surfaced to your team for review — or run Belvedere in proposal mode, where every change requires human approval before it ships. You choose the level of autonomy.

  • High-confidence fixes applied automatically — no 3 a.m. pages
  • Low-confidence changes routed to your team for review
  • Proposal mode available — human approves every change before deploy
  • Full audit trail on every action, automatic or approved
app.clearfracture.ai/observability
Live
ObservabilityAll nominal
99.9%Health
2.1sLatency
7Auto-heals
Schema drift detected — auto-healedHUMINT Merge · 2 min ago
Latency spike above thresholdIdentity Graph · 8 min ago
New source column discoveredGEOINT Ingest · 15 min ago
7 auto-resolved
0 manual actions
Architecture

Three Intelligent Arms. One Unified Platform.

Belvedere operates as a multi-agent system with three intelligent “arms” — knowing, doing, and watching. Processing logic is maintained separate from its implementation, making understanding accessible to non-developers and platform migrations painless.

01 — Knowing

Knowledge Arm

Continuously explores your systems, tools, and data sources to understand where data lives, what it means to different teams, how it flows, and what governs it. Definitions, relationships, and context are stored — so knowledge persists even when people leave.

  • Auto-discovers sources and schema
  • Maps lineage, context, and governance
  • Living knowledge graph of your environment
02 — Doing

Workflow Arm

Designs, tests, and deploys deterministic, auditable pipelines with enforced contracts between data producers and consumers. Context carries through every transformation layer — traceable, affordable at scale, and already trusted by the enterprise.

  • Generates deterministic, auditable code
  • Deploys on your existing infrastructure
  • Goal-oriented — declare what, not how
03 — Watching

Observability Arm

Monitors every pipeline, data product, and integration point in real time. When something drifts — a schema change, a definition that no longer matches its contract, a data quality anomaly — Belvedere detects it, diagnoses the root cause, and self-heals before it impacts downstream consumers.

  • Real-time pipeline health monitoring
  • Automatic schema-drift detection and repair
  • Self-healing with full audit trail
Agent-Native Operations

Give Your Existing Agent Swarm a Chief Data Officer.

Connect to the stack you already run

Belvedere works inside your existing enterprise and agent architecture, so value increases without a rip-and-replace program.

Give every agent shared, governed context

Clean data products, contracts, and lineage-aware context stay intact across transformations instead of being lost in prompts and pipeline code.

Make every agent output easier to trust

Auditable, verifiable outputs give your teams the confidence to use agent-driven decisions in real operational workflows.

Belvedere does not ask you to replace the agents, models, or orchestration layers you've already deployed. It operates inside that environment as the trusted data and governance layer, giving every agent access to current, structured, lineage-aware context instead of brittle prompts, stale retrieval results, or disconnected source systems.

Belvedere can act as the Chief Data Officer for your agent swarm, giving every agent the equivalent of a team of data engineers and data stewards. It publishes clean data products, contracts, and governed context that agents can use directly, so their decisions are informed by context that is data-driven, auditable, and verifiable. Let Belvedere operate autonomously where confidence is high, and require human review where the stakes are higher.

Security Model

Verifiable by design. AI speed and intelligence, with deterministic results you can trust.

No hallucinations

Deterministic, verifiable code output — not probabilistic guesses

No vendor lock-in

Portable pipeline logic that runs anywhere your infrastructure lives

Automation you can trust

Every action is logged, explainable, and fully auditable

Operates your tools

Maximizes your existing IT investments instead of replacing them

Belvedere operates your tools on your behalf — its agents never touch mission data directly. They write verifiable code that runs inside your environment, using data contracts and system models to know what the data means before they act. No hallucinations. No black boxes. AI that produces deterministic, auditable, repeatable output you can verify before it ever reaches production.

Get Started

Ready to See Belvedere in Action?

We'll show you Belvedere operating on a live data environment — not slides. See how declarative data ops delivers trusted results in minutes.

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Latest Articles

From the ClearFracture Team

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

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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.”

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A Write-Audit-Publish (WAP) Skill for Agentic Data Pipelines

A Write-Audit-Publish (WAP) Skill for Agentic Data Pipelines

Haydn StraussHaydn Strauss4 min readData EngineeringPublished July 14, 2026

AI agents are great at building data pipelines that look like they work until you dig into the results.

Write-audit-publish (WAP) helps fix that. Stage the data, audit it against a declared contract, and only publish once every clause passes. Netflix popularized this pattern in 2017.

A pipeline that finishes successfully is not the same as one whose output is correct.

We’ve built a number of internal skills to make our own data pipelines safer, and this one felt useful enough to release as a free WAP skill for coding agents.

The first test was on Netflix’s Top 10 dataset. The initial run stopped at the gate. Our contract said every film should have “N/A” as the season title, but the agent found nine rows that didn’t match. The contract was wrong, not the data. We fixed it, started a fresh run, and the second attempt published cleanly, with the total reconciling to exactly 185,656,120,000 hours viewed.

We ran it again on an NFL play-by-play pipeline (converting play description strings into structured stat tables). It caught a parser bug that left 1,723 completed passes without matching receptions, exactly the kind of thing a "successful" run hides.

Below, we dig a bit more into how the skill works. Give it a read, or point your coding agent at this URL and try it yourself.

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