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VERITAS

The Human + AI Truth Engine

Fighting Misinformation with Transparency

By Tobyn Bunch

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Logo: shield + checkmark / owl

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💡 The Problem

Misinformation is everywhere — and current solutions are flawed.

▸ False claims spread faster than the truth on social media

▸ Fact-checkers are too slow to keep up with viral content

▸ AI systems are black boxes that give answers without showing their work

▸ People don't know who or what to trust

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Split screen: false social feed vs. confused person

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🏛️ Our Inspiration

Veritas is the Latin word for "truth."

Our mission: to uncover truth in a world drowning in misinformation.

We wanted to build a fact-checking system that:

▸ Combines the speed of AI with the judgment of humans

▸ Shows its work — no black boxes

▸ Finds real evidence from trustworthy sources

▸ Returns a transparent score anyone can understand

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Dictionary 'Veritas' entry / justice statue

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🔍 What It Does

Veritas takes any claim and returns a truth score with evidence.

▸ Users enter a claim (e.g., "Vaccines cause autism")

▸ Veritas searches .edu and .gov sites for evidence

▸ It extracts the full content from those sources

▸ Claude AI analyzes the evidence

Returns a 0–100 credibility score with:

▸ ✅ Clear reasoning (why the score was given)

▸ 🏷️ Status badge (Verified, False, Disputed, Uncertain)

▸ 📚 Source citations (where evidence came from)

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Veritas interface: claim, score, reasoning, sources

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🏗️ The 3-Agent Architecture

Three AI agents working together.

🔍 Searcher Agent

Port 5001

▸ Finds trustworthy sources

▸ Priority: .edu, .gov, research, fact-checking

▸ Tools: DuckDuckGo API, trust-scoring

▸ Output: Ranked URLs + snippets

📄 Extractor Agent

Port 5002

▸ Reads full content from sources

▸ Tools: BeautifulSoup, browser headers, retries

▸ Challenge: Bypasses 403s & rate limits

▸ Output: Clean, readable text

🧠 Judge Agent

Port 5003

▸ Analyzes evidence & returns a score

▸ Tools: Claude AI, structured prompting

▸ Output: Score 0-100, reasoning,

▸ status, sources

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🔄 How It Works — The Flow

👤 User submits a claim

↓

🔍 Searcher finds .edu / .gov sources

↓

📄 Extractor reads full content

↓

🧠 Judge analyzes with Claude AI

↓

📊 Return: Score + Reasoning + Sources

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🛠️ How We Built It

Technology Stack

Component

Technology

Language

Python 3.12

Web Framework

Flask

AI Model

Claude AI (Anthropic)

Web Search

Browserbase API

Content Extraction

BeautifulSoup, lxml

Monitoring

Arize OTEL

Public Access

Ngrok

Version Control

GitHub

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Tech stack diagram with logos

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⚠️ Challenges We Faced

Our biggest obstacles — and how we solved them

Challenge

What Happened

How We Fixed It

Claude Model Deprecation

Model returned 404 error

Updated to claude-4-haiku-20250514

Arize OTEL Setup

BatchSpanProcessor silently failed

Switched to SimpleSpanProcessor

Ngrok URLs

Public URL changed on restart

Added health check, documented updates

403 Errors

Websites blocked our requests

Browser-like headers + retry logic

Source Quality

Low-quality search results

Trust-scoring (.gov=100, .edu=95)

API Rate Limits

DuckDuckGo throttled requests

Added delays and fallbacks

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🏆 Accomplishments We're Proud Of

▸ Built a working 3-agent system in a single hackathon

▸ Real .edu/.gov source finding with trust-scoring

▸ Anti-blocking extractor that bypasses 403 errors

▸ Claude AI integration with intelligent reasoning

▸ Transparent output: score, reasoning, and sources

▸ Modular design — each agent runs independently

▸ Full monitoring with Arize OTEL tracing

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Trophy / checkmark icons per achievement

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📚 What We Learned

▸ AI alone isn't enough — human judgment + transparent evidence map show the trust in the websites

▸ Monitoring is critical — Arize OTEL revealed what agents were doing

▸ API version management matters — Claude models get deprecated

▸ Modular systems are easier to debug — test each agent independently

▸ Source quality > quantity — one .edu beats ten random blogs

▸ Anti-blocking is essential — sites expect browser-like behavior

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Lightbulb / book icons per lesson

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🚀 What's Next for Veritas

Future improvements we're excited about

Feature

Description

Browser Extension

Fact-check any claim on any webpage with one click

On-Chain Verification

Store fact-checks on blockchain for transparency

Custom Evaluators

Users create their own evidence criteria

Multi-Language

Fact-check in languages beyond English

Mobile App

Fact-check on the go

Human Consensus Layer

Trusted friends + crowd voting to correct AI

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Roadmap / timeline graphic

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🦊 The Verdict

Veritas: AI for speed, people for judgment, transparency for trust.

We built a fact-checking system that:

▸ 🔍 Finds real evidence from trustworthy sources

▸ 🧠 Analyzes with intelligent AI reasoning

▸ 📊 Returns a clear, transparent score

▸ 🏷️ Shows its work with source citations

The result: a tool that fights misinformation with transparency.

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Veritas logo / hero shot

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VERITAS

Thank You

Uncovering truth in a world drowning in misinformation 🦊