From prototype to production for grounded agentic research.

CloudRaven Labs helps teams find a credible path to production with AI-powered research systems, enrichment workflows, agents, and coding toolkits built for provenance, evaluation, and practical use.

Returning collaborators and client reviewers can sign in directly. New contributors can create an account and request to join the program.

Research SystemsEvidence-first workflows

CloudRaven Research Solutions

Generative research solutions for real workflows

Explore CloudRaven Labs’ solutions that demonstrate purpose-built AI tools for human-in-the-loop enrichment. Examples include experiences for job seekers, community leaders, and geospatial analysts.

Job seekers

ResumeRavenPro

Generative job assistance

AI-enhanced resume optimization and tailored career insights to help candidates move faster and present stronger applications.

Explore service

Community leaders

Project WellTrend

Neighborhood wellbeing insights

Assess community-level trends in poverty, internet access, and other indicators with human-in-the-loop research flows.

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Geo analysts

TrendSights.io

Agentic trends research

Spot trends with agentic tools, research observability, and ambient workflows designed for grounded insight generation.

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CloudRaven Latest

Latest news and notes from CloudRaven Labs program teams

Follow on X and LinkedIn for the latest opportunities, updates, and team news.

March 25, 2026

Narrative-as-Code: How CloudRaven Labs Uses Codex and VS Code to Build Human-Led Story Systems

Storytelling does not have to stay trapped in scattered notes, disconnected docs, and fragile memory. Narrative-as-code is a practical way to structure creative work so human-led agents can help writers move faster without flattening the soul of the story.

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March 23, 2026

State Machines, Not Endless Loops: A Better Agent Pattern for ResumeRavenPro and Channel Systems

The strongest agent systems are not open-ended loops. They use explicit orchestration, bounded reasoning, and stateful execution to drive trustworthy workflows in products like ResumeRavenPro and channel sales platforms.

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January 20, 2026

Deep and Ambient Agents for Trustworthy Federal Data: CloudRaven Labs in the 2026 TOP Sprint

CloudRaven Labs is joining The Opportunity Project 2026 sprint to explore deep, ambient agent patterns that improve LLM accuracy with federal open data, stronger provenance, and better user outcomes.

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The Opportunity Project • CloudRaven Workspace

Improve LLM accuracy and data usability with authoritative tools, agents, and MCP integration, built around reproducible prompts.

A sprint-style collaboration to prototype real, human-in-the-loop workflows that pull from authoritative Census sources and keep provenance front and center. The current plan is to begin team work in mid-April 2026, starting the week of April 13, 2026.

CloudRaven Labs

Agentic research services with citations and provenance

Developing agentic research services on federal open data with a focus on authoritative citations, reproducible results, and data provenance.

U.S. Census COIL

Partnership to improve how LLMs use federal data

Working with Census Open Innovation Labs to improve how LLMs serve accurate, reliable information through agentic workflows using the Model Context Protocol (or an API layer).

Current Focus

trendsights.io as a reference implementation

Demonstrating how US Census API + MCP server integration can deliver trustworthy data to agentic researchers with citations, efficient context usage, and high accuracy.

Sprint objective

Launch trendsights.io with agentic, human-in-the-loop research use cases that demonstrate:

Authoritative citations
Efficient context-window usage
Reproducible results and provenance

Where collaborators can help right now

Refine MCP + agentic integration architecture for Census datasets
Research and prioritize use cases for trend signals and data products
Create wireframes for data visualization components
Develop prototype prompts that demonstrate citation quality
Test context window optimization strategies
Document reproducibility and provenance processes

Target topics and questions

Who are the target audiences for trend signals, research derivatives, and data products?
What are the target problems and pain points for the core audiences and use cases?
Which user journeys require authoritative citations from Census datasets?
What context-window strategies minimize tokens while preserving fidelity?
Which datasets outside Census APIs are essential complements?
How can we ensure trendsights.io demonstrates clear provenance for all data?
What visualization approaches best communicate data reliability to users?

Resources

Quick links for MCP, Census APIs, and the sprint program

Resource	Note
Model Context Protocol (MCP)	Open standard to connect tools and data to LLMs reliably.
Census Data APIs	Official endpoints, metadata, and API user guide.
US Census API - MCP Server	Bring official Census Bureau statistics to AI assistants via MCP.
The Opportunity Project	Program details and sprint challenges from COIL.
CloudRaven Labs: trendsights.io	Project site and development documentation.

Join as a collaborator

Help with architecture, UX, prompt design, evaluation, or docs. We’ll plug you into a task area quickly.

Join the workspace View project docs

Team members will be finalized and posted by April 10, 2026.