Below is a Devpost / hackathon–ready write-up, written directly from your architecture and pipeline, techy but clear, and easy for judges to scan. You can paste this as-is.


💡 Inspiration

Immigration information is scattered across government websites, forums, and outdated blogs. People spend hours researching, still unsure if they are missing a step or risking their legal status. We wanted to build a system that acts like a real-time pulse of immigration rules—constantly monitoring official sources and turning complexity into clarity.


⚙️ What it does

ClarityPulse is a real-time immigration roadmap generator.

Given a user’s current visa, target visa, and basic personal context, it:

  • Generates a step-by-step immigration roadmap
  • Calculates timelines, deadlines, and total duration
  • Breaks down government fees, legal costs, and documents
  • Highlights decision points with recommendations
  • Identifies risks and when to consult an immigration attorney
  • Provides citations from official government sources

All outputs are structured, traceable, and ready to use.


🏗️ How we built it

We built ClarityPulse as a parallel AI pipeline using three AI services:

  1. OpenAI (Search Strategy Generator) Understands the user’s immigration scenario and generates:
  • Targeted search strategies
  • Relevant government websites
  • Key legal and procedural terms
  1. Parallel Data Gathering
  • Perplexity retrieves structured, up-to-date immigration data with citations
  • Firecrawl scrapes official government websites (USCIS, DOL, State Dept) in parallel
  1. OpenAI (Final Synthesis Engine) Combines all sources into a single, comprehensive immigration roadmap, including timelines, costs, decisions, and legal guidance.

The system outputs four structured JSON files, with a final production-ready roadmap as the main artifact.


🧗 Challenges we ran into

  • Fragmented and inconsistent immigration data
  • Balancing authoritative sources with recent web information
  • Ensuring structured, deterministic outputs from LLMs
  • Parallelizing external API calls while keeping latency low
  • Avoiding legal hallucinations and ensuring proper citations

🏆 Accomplishments that we're proud of

  • Built a fully parallel, end-to-end AI pipeline
  • Combined official government data + recent web intelligence
  • Generated actionable outputs (dates, costs, decisions—not summaries)
  • Included explicit attorney consultation triggers
  • Achieved ~40 seconds end-to-end execution time
  • Designed outputs that are UI- and production-ready

📚 What we learned

  • Parallel AI workflows dramatically improve both speed and reliability
  • Structured outputs are critical for trust in legal and compliance domains
  • Combining multiple AI services produces far better results than a single model
  • Clear decision points matter more to users than raw information
  • Citations are essential for credibility in high-stakes domains

🚀 What's next for ClarityPulse

  • User dashboards to track immigration progress over time
  • Live alerts for rule changes, deadlines, and processing times
  • Country-agnostic expansion beyond the U.S.
  • Attorney and advisor integrations
  • Personalized scenario simulations (best-case vs worst-case paths)

ClarityPulse aims to become the real-time heartbeat of immigration journeys, replacing confusion with clarity.


Built With

  • apifirecrawl
  • apis
  • cli-based
  • data
  • dotenv
  • engineering
  • json
  • openai
  • parallel
  • perplexity
  • pipeline
  • processing
  • prompt
  • python
  • rest
  • validation
Share this project:

Updates