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Tutorials, deep dives, and guides for building AI agents with verified intelligence.
Teach Your Agent to Stop Hallucinating
One command installs two skills that teach any AI agent when to verify claims and when to use live data instead of guessing. Works with Claude Code, Cursor, Copilot, and Codex.
Consensus Verification: Six Models, One Verdict
Every AI verification service uses one model. We query Claude, GPT, Gemini, DeepSeek, Llama, Grok — plus live data from Yahoo, FRED, and SEC EDGAR. Six models guess. VEROQ knows.
The Missing Hand: Output Verification for Managed Agents
Anthropic's Managed Agents architecture solves reliable execution. But nobody verifies what the agent produced. Here's how to add a verification 'hand' to any agent pipeline.
Build Agentic Workflows That Verify Every Step
Your AI agent can search, analyze, and generate. But can it prove its answers? Agentic workflows chain multiple intelligence steps — each one verified before the next runs.
Sub-20ms Trading Signals from 23 Data Sources — The /fast/ Tier
Pre-computed intelligence signals for systematic trading. CFTC positioning, social sentiment, SEC insider trades, Wikipedia attention, and more — all in one API call, updated every 5 minutes.
Fact-Check X Posts and Get Social Sentiment — New MCP Bridge
Your AI agent can now search X, analyze social sentiment, and verify claims in trending posts. Two sentiment layers with divergence detection. One npm install.
Karpathy Wants an LLM Knowledge Base Product. Here's the Missing Layer.
Andrej Karpathy described the ideal LLM knowledge base workflow — ingest, compile, query, lint. But there's no verification layer. Your wiki can be internally consistent and completely wrong.
Why Your RAG Pipeline Needs Two Verification Layers
Your RAG system can be perfectly grounded and still completely wrong. Groundedness catches hallucinations. Factual verification catches reality. You need both.
Self-Hosted Shield: LLM Verification Inside Your VPC
Run VeroQ Shield on your infrastructure. Your models, your data, nothing leaves your network. Two verification modes: groundedness (local) + factual (opt-in). Docker deploy in 30 seconds.
Ship Verified AI: Add VEROQ to Your CI/CD Pipeline
Every PR fact-checked. Contradicted claims block the deploy. Verification receipts for compliance. One GitHub Action, zero hallucinations in production.
Introducing VEROQ — The Truth Protocol for Agentic AI
5 agents verify every answer before your agent sees it. Evidence chains with source reliability, confidence decomposition, verification receipts, and a multi-agent swarm. The truth protocol for agentic AI.
Introducing the VEROQ CLI — Financial Intelligence From Your Terminal
12 commands. 891 tickers. JSON-first for agents, human-readable when you need it.
Build an Autonomous Trading Agent with Python in 10 Minutes
From zero to a working trading agent that screens tickers, checks sentiment, verifies claims, and sets alerts. Copy-paste Python code with the VEROQ SDK.
Best APIs for Algorithmic Trading Agents in 2026
A practical comparison of trading data APIs for AI agents. Prices, sentiment, technicals, screeners, and intelligence — what each API offers and what it costs.
How to Add Sentiment Analysis to Your Trading Bot
Numeric sentiment scores per entity, sentiment history, shift detection, and composite trading signals. Turn headlines into quantitative signals your bot can trade on.
How to Add Real-Time News to Your RAG Pipeline
Most RAG pipelines have a freshness problem. Here's how to add verified, confidence-scored intelligence to your vector database so your agent always has current context.
The Complete Guide to MCP Servers for AI Agents
What MCP servers are, how they work, and which ones are worth connecting. Practical guide for Claude Desktop, Cursor, and any MCP-compatible client.
How Trading Agents Can Pay for Intelligence Autonomously
Your trading agent can now discover, evaluate, and pay for intelligence without human intervention. No API key, no signup, no friction.
How to Add Verified News Intelligence to TradingAgents
Replace raw news feeds in the TradingAgents framework with confidence-scored intelligence from VEROQ. Better sentiment data, bias detection, and structured predictions for your trading agents.
VEROQ Now Works with Zapier, Make, and n8n
Connect VEROQ to 5,000+ apps without writing code. Automate intelligence workflows with triggers for new briefs, watchlist matches, and trending entities.
Introducing /forecast: Structured Predictions for AI Agents
Ask what's likely to happen next. Structured predictions with confidence scores, evidence chains, and falsification criteria — powered by analysis across thousands of verified briefs.
Set Up Intelligent Alerts: Watchlists and Monitors
Watch any entity, topic, or category. Get notified via webhook, email, or in-app when matching intelligence publishes. Agents can create programmatic monitors with callback URLs.
Agent Memory: Your Agent Remembers What It Already Read
Create sessions, mark briefs as read, and get filtered feeds that skip already-consumed content. No more duplicate processing.
How VEROQ Became One of the First APIs to Support Stripe's Machine Payments Protocol
Your AI agent can now pay for intelligence autonomously. No signup, no API key, no friction. Agents discover, pay, and get verified intelligence in a single flow.
Your AI Agent Can't Fact-Check. Now It Can.
Every AI agent has the same blind spot: it can retrieve information, but it can't tell you if that information is true. /verify closes that gap.
Introducing /verify: Fact-Check Any Claim with One API Call
Introducing /verify — fact-check any claim against thousands of verified intelligence briefs. Four verdicts: supported, contradicted, partially supported, unverifiable.
Inside the Signal Radar: How We Built a Real-Time Intelligence Command Center
Top signals ranked by confidence, entity relationships mapped, story clusters with cascading effects, source bias visualization, live feed by vertical, and living briefs that get richer over time.
Track Any Entity Across the Intelligence Cycle
14-day mention timelines, automatic trend detection, and peak analysis for any entity across 18 verticals. Built for AI agents and analysts.
Give Claude Desktop Real-Time Intelligence with MCP
Set up real-time world knowledge in Claude Desktop in 60 seconds. Zero-install MCP server with 44 tools for intelligence, trading, market data, and more.
Confidence Scoring: How VEROQ Knows What to Trust
Deep dive into how VEROQ calculates confidence scores for intelligence briefs. Multi-factor trust assessment for AI agents that need reliable information.
Build a Daily Intelligence Digest Agent with GitHub Actions
Set up an automated daily intelligence briefing agent using GitHub Actions and the VEROQ API. Runs free, delivers to Slack every morning.
Same Story, 6 Different Spins: How Outlets Frame the Same Event
We analyzed how major outlets covered the same story. The framing differences are striking — and they matter for AI agents ingesting world events.
How to Add Real-Time World Knowledge to Your LangChain Agent
Step-by-step guide to adding verified intelligence to LangChain agents. Tools, RAG retriever, and trending entity monitoring with confidence scoring.
Why Your AI Agent Needs Bias Detection
Knowledge APIs feed your agent information — but whose perspective? Bias detection catches loaded language, framing differences, and omissions before your agent acts on skewed intelligence.
Get Breaking Intelligence in Your Slack Channel in 2 Minutes
Push verified intelligence briefs to Slack or Discord with VEROQ webhooks. Formatted messages with confidence scores, categories, and source counts.
Tavily vs VEROQ: Which Knowledge API Should Your AI Agent Use?
Detailed comparison of Tavily and VEROQ for AI agents. Confidence scoring, bias detection, pricing, and integration coverage.
Build an Intelligence Agent in 5 Minutes
Go from zero to a working AI intelligence agent with the VEROQ Python SDK. Start with a curl command, end with a full briefing function.