How to Build a Personal OSINT Agent with AI: Track Anyone, Any Topic, Automatically

ByL.B. Kaelin

How to Build a Personal OSINT Agent with AI: Track Anyone, Any Topic, Automatically

By the end of this guide, you will have a working AI agent that monitors any name, domain, organization, or topic you care about — and pings you on Slack or Telegram the moment something new appears. No manual Googling. No refreshing bookmarks. No digging through RSS feeds at 2 AM. The agent does the looking. You get the signal.

This is not a theoretical walkthrough. Every configuration file, every API setting, and every schedule below is something you can copy, paste, and deploy today. If you have 30 minutes and a few dollars for API credits, you can have this running by the time your coffee gets cold.

What OSINT Is (And What It Isn’t)

OSINT stands for Open Source Intelligence: the practice of gathering and analyzing information from publicly available sources. It is legal by design. If a piece of information is published on a public website, indexed by a search engine, or broadcast on a public forum, it is fair game for OSINT collection.

OSINT practitioners include journalists investigating a story, researchers tracking disinformation campaigns, competitive intelligence analysts studying rival companies, security professionals monitoring threat actors, and ordinary people keeping tabs on their own digital footprint. The US intelligence community formalized OSINT as a core discipline decades ago, but the tools have only recently become available to anyone with a laptop and an internet connection.

What OSINT is not: it is not hacking, not social engineering, not accessing private accounts, and not surveillance of individuals without legal authorization. The boundary is simple — if you need a password, a warrant, or a login you do not own, it is not OSINT.

What an AI OSINT Agent Does

Manual OSINT is tedious. You open a browser tab. You type a search query. You scan the results. You open another tab. You repeat. A person doing this full time might check 20 sources a day across two or three topics. An AI agent doing the same work can check hundreds of sources across dozens of topics, every few hours, without ever losing focus.

An AI OSINT agent replaces the looking part of intelligence gathering. You define what matters — a person’s name, a company, a domain, a regulatory term, a geopolitical event — and the agent runs on a schedule, searches the web, reads new content, and decides whether anything is worth your attention. It surfaces only new developments, discarding everything it has already reported. The result is a low-noise intelligence feed delivered to your messaging app of choice.

This is not a replacement for deep analysis. The agent is a collector and a filter. You remain the analyst. The difference is that instead of spending your time gathering, you spend it thinking.

The Tool Stack: What You Need

The stack is four components, none of which are proprietary or expensive:

  1. OpenClaw — the open-source agent platform that runs your OSINT agent. It handles scheduling, tool execution, memory, and delivery. Free and self-hosted. 347K GitHub stars.
  2. A web search API — Brave Search API or Tavily API. These give your agent the ability to search the live web and fetch relevant results.
  3. An LLM — any modern language model that runs on OpenClaw. DeepSeek V3, GPT-4o, Claude Sonnet, or a local model through Ollama all work. For a monitoring agent, DeepSeek V3 at token cost is the most economical option.
  4. A VPS or always-on machine — the agent needs to run 24/7. A $6/month Linux VPS from a provider like DigitalOcean, Hetzner, or Linode is sufficient. Or a Raspberry Pi at home, if you do not mind the power draw.

That is it. No databases. No message queues. No container orchestration. OpenClaw handles the infrastructure so you do not have to think about it.

Step 1: Set Up Web Search in OpenClaw

OpenClaw supports plugin-based web search. You configure an API key in openclaw.json, and the agent gains the ability to search the web as a native tool.

Option A: Brave Search API

Brave Search runs its own index and does not depend on Google or Bing. It is cheap — roughly $5 per month for 2,000 queries, which is plenty for a personal monitoring agent. Sign up at brave.com/search/api/ to get an API key.

In your OpenClaw configuration file (openclaw.json), add the web search plugin:

{
  "openclaw": {
    "plugins": {
      "entries": {
        "web-search": {
          "location": "https://github.com/openclaw/plugin-web-search",
          "enabled": true,
          "config": {
            "provider": "brave",
            "apiKey": "YOUR_BRAVE_API_KEY"
          }
        }
      }
    }
  }
}

Option B: Tavily API

Tavily is designed specifically for AI research agents. Its results are cleaned, deduplicated, and focused on relevant content rather than SEO spam. Pricing starts at free tier (1,000 queries/month) and goes to $20/month for 5,000 queries. For news monitoring, Tavily’s results tend to be better than general web search because the API prioritizes timeliness. Sign up at tavily.com.

{
  "openclaw": {
    "plugins": {
      "entries": {
        "web-search": {
          "location": "https://github.com/openclaw/plugin-web-search",
          "enabled": true,
          "config": {
            "provider": "tavily",
            "apiKey": "YOUR_TAVILY_API_KEY"
          }
        }
      }
    }
  }
}

Restart OpenClaw after saving the config file. Verify the plugin loaded by running openclaw gateway status and checking the plugin list. You can test the search tool by asking your agent a simple question like “What is the latest news about DeepSeek?”

Step 2: Define Your Agent’s Role (SOUL.md)

Every OpenClaw agent has a SOUL.md file in its workspace. This file defines who the agent is and what it does. For an OSINT monitoring agent, the SOUL.md should be specific about what topics to track and how to handle findings.

Create a file at /path/to/agent/workspace/SOUL.md with content like this:

# SOUL.md - OSINT Monitoring Agent

You are a research intelligence agent. Your job is to monitor the topics,
names, domains, and organizations listed in TARGETS.md and surface new
developments to your operator.

## Core Rules

1. Never report the same finding twice. Check MEMORY.md before sending
   any alert. If a finding is already in MEMORY.md, skip it.

2. For each target in TARGETS.md, run a web search query. Read the top
   3-5 results using web_fetch. Extract factual, newsworthy information.

3. For each new finding: summarize it in 2-3 sentences. Include the
   source URL. Rate relevance as HIGH, MEDIUM, or LOW.

4. After reporting new findings, append them to MEMORY.md with a
   timestamp so they are not reported again.

5. If no new findings exist for a target, skip it silently. Do not
   report "nothing found."

## Output Format

For each new finding, use this format:

**NEW FINDING: [Target Name]**
**Relevance:** HIGH|MEDIUM|LOW
**Source:** [URL]
**Summary:** 2-3 sentence factual summary.
**Timestamp:** ISO-8601

## Tone

Neutral, factual, concise. Do not editorialize. Do not speculate.
Report only what the public sources say. Flag uncertainty explicitly.

Replace the targets section with whatever you actually want to track. The key design choice: require the agent to check MEMORY.md on every run. That prevents the single most common failure of monitoring agents — reporting the same article every cycle.

Step 3: Create Your TARGETS.md File

TARGETS.md is your intelligence tasking document. Every line defines something the agent monitors. Format matters because the SOUL.md instructs the agent to parse this file at the start of each run.

Create TARGETS.md in the same workspace:

# TARGETS.md - Monitored Topics

## People
- Elon Musk
- Sam Altman
- [Your Own Name or Brand]

## Companies
- OpenAI (latest funding, leadership changes, product launches)
- Anthropic (latest funding, Claude releases, safety research)
- DeepSeek (model releases, performance benchmarks, cost changes)

## Organizations
- NIST (AI standards, cybersecurity frameworks)
- European Commission Digital Policy (AI Act, DSA enforcement)

## Regulatory Terms
- AI Act
- SEC cybersecurity disclosure rules
- FINRA AI guidance

## Domains
- redrook.ai
- [competitor-domain.com]

This file is meant to evolve. Add targets as your interests shift. Remove targets that go quiet. The agent reads it fresh every run, so editing it is effectively reprioritizing your intelligence collection in real time.

Step 4: Configure the Monitoring Cron (HEARTBEAT.md)

OpenClaw uses HEARTBEAT.md as its cron scheduling mechanism. The HEARTBEAT.md defines a prompt that runs on a timer. For OSINT monitoring, you want the agent to check for new mentions every 4-6 hours — frequent enough to catch breaking news, infrequent enough to stay under API rate limits and token budgets.

Create HEARTBEAT.md in the workspace:

# HEARTBEAT.md - OSINT Collection Schedule

## Schedule
Pattern: every 4 hours (recommended for daily monitoring)
Run this task: at minutes 0, 4, 8, 12, 16, 20 (each run triggers one check)

## Prompt (executed on every heartbeat)

1. Read TARGETS.md to get the current list of topics to monitor.
2. Read the last entry in MEMORY.md to determine the last check time.
   If MEMORY.md is empty or you cannot determine the last check, use
   24 hours ago as the window.
3. For each target in TARGETS.md:
   a. Search the web for new mentions since the last check time.
   b. Read the top results using web_fetch.
   c. Cross-reference each potential finding against MEMORY.md.
   d. Report only findings that are NOT already in MEMORY.md.
4. Format all new findings using the NEW FINDING format from SOUL.md.
5. After reporting, append each new finding to MEMORY.md with its
   ISO-8601 timestamp.
6. If zero new findings across all targets, do nothing.

The deduplication logic is the critical part. Every cycle, the agent reads MEMORY.md to see what has already been reported. It searches for content published since the last check. It reads results, filters out duplicates, and only sends what is genuinely new. Without this step, your Slack channel fills with the same articles every six hours.

MEMORY.md will accumulate over time. A well-maintained MEMORY.md for an OSINT agent tracking 10-15 targets over 6 months might be 300-500 entries. That is fine; modern LLMs handle context of that size easily.

Step 5: Set Up Delivery (Slack or Telegram)

OpenClaw can deliver agent output to Slack or Telegram directly. Both channels are supported natively. Pick the one you already use.

Slack

Add the Slack plugin to openclaw.json:

{
  "openclaw": {
    "plugins": {
      "entries": {
        "slack": {
          "location": "https://github.com/openclaw/plugin-slack",
          "enabled": true,
          "config": {
            "botToken": "xoxb-your-bot-token",
            "appToken": "xapp-your-app-token",
            "channel": "#osint-feed"
          }
        }
      }
    }
  }
}

Create a dedicated channel (like #osint-feed) so the intelligence feed does not clutter your main team channel. The agent posts findings there, and you can react to flag items for follow-up.

Telegram

For Telegram, you need a bot token (from @BotFather) and your chat ID:

{
  "openclaw": {
    "plugins": {
      "entries": {
        "telegram": {
          "location": "https://github.com/openclaw/plugin-telegram",
          "enabled": true,
          "config": {
            "botToken": "YOUR_BOT_TOKEN",
            "chatId": "YOUR_CHAT_ID"
          }
        }
      }
    }
  }
}

Telegram is the more common choice for solo OSINT practitioners because it does not require a workspace or team setup. A private channel with just the bot and you is all you need.

Real Use Cases: What People Actually Monitor

The flexibility comes from TARGETS.md. Change the list, and the agent shifts focus entirely. Here are real patterns people use:

  • Competitor intelligence. Track a rival company’s product announcements, funding rounds, leadership hires, and regulatory filings. Get notified within hours of press coverage.
  • Personal brand monitoring. Monitor your own name, your company name, your domain, and your projects. Catch mentions that need responses — good press, bad press, impersonations.
  • Journalist source tracking. Monitor specific people, organizations, or topics relevant to a story you are investigating. The agent becomes your research assistant, working 24/7 on background.
  • Regulatory watch. Track agencies like the SEC, FTC, FINRA, or European Commission for new guidance, enforcement actions, or proposed rules that affect your industry.
  • SEC filing monitoring. Set targets like “SEC filings mentioning [company name]” and the agent catches 8-Ks, 10-Qs, and material event announcements that mention your target.
  • Domain monitoring. Track domains you care about for significant content changes — or domains you do not own but want to watch for competitive or legal reasons.
  • Cryptocurrency and blockchain. Monitor project names, wallet addresses mentioned in public contexts, protocol upgrades, and governance proposals.

The agent does not replace domain expertise. It replaces the grunt work of checking sources repeatedly.

Cost Breakdown: What This Costs Per Month

Here is the honest, itemized monthly cost of running an OSINT monitoring agent full time:

Item Minimum Comfortable Notes
VPS (Linux, 1-2 GB RAM) $4 $12 Hetzner CAX11 or DigitalOcean basic droplet
Brave Search API $0 $5 Free tier ~2,000 queries; paid at $5 for same
Tavily API (alternative) $0 $5-20 Free tier 1,000 queries; paid from $20
LLM token costs (DeepSeek V3) $1 $5 ~$0.50/M input tokens; monitoring agent uses ~50K tokens per run
Domain (optional) $0 $1/mo amortized If you want a clean URL for agent access
Total $5-6 $23-38 All figures in USD

At the comfortable tier ($23-38/month), you get the best web search provider, a responsive VPS, and enough LLM budget for 10-15 runs per day. At the minimum tier ($5-6/month), you get functional monitoring at lower frequency on a shared-VM VPS with the free Brave tier.

These costs assume self-hosting on a raw VPS. If you use OpenClaw Cloud or another managed service, add the platform fee. The self-hosted route is the most cost-effective.

Limits and Honest Caveats

An AI OSINT agent is powerful but not magic. Here are the hard limits:

  • Search engine dependency. The agent can only find what search engines index. If a source blocks crawlers, requires JavaScript rendering, or lives on the dark web, the agent is blind to it. Most web search APIs return pre-indexed results, not live crawl results.
  • False positives. Name matching is imprecise. A search for “Elon Musk” returns articles about his companies, his tweets, opinion pieces, parodies, and entirely unrelated people named Elon Musk. Topic filtering by an LLM helps but is not perfect. Expect false positives, especially in the first few days of tuning a new target.
  • False negatives. The agent reads 3-5 results per search. If a major development appears on result page 2 or 3, the agent may miss it. Increasing the result count increases token cost. The 3-5 result default is a compromise between coverage and cost.
  • Paywalls. The web_fetch tool cannot bypass paywalls. It reads publicly accessible content. If a crucial development breaks behind a subscription, the agent may find the headline (from a search snippet) but cannot read the article body.
  • Latency. A complete run across 10 targets takes 3-8 minutes depending on LLM speed, API response time, and page load times. For most monitoring purposes, 4-hour cycles are fine. If you need sub-minute alerts for breaking news, this architecture is not the right fit.
  • Context drift. Over weeks, MEMORY.md grows. Large memory files increase token consumption and can cause the agent to lose focus. Periodically archive old entries and trim MEMORY.md to the most recent 100-200 findings.
  • No source prioritization. The agent treats all search results equally. It does not know that Reuters is more authoritative than a random blog. The human analyst must make those qualitative judgments.

Legal and Ethical Note

This guide describes monitoring of publicly available information only. OSINT conducted on public sources is legal in virtually all jurisdictions. The tools and techniques described here are used by journalists, researchers, security professionals, and regulators every day.

Do not use this for:

  • Stalking, harassment, or intimidation.
  • Accessing private accounts, private profiles, or non-public content.
  • Monitoring individuals without a legitimate purpose (journalism, security, or your own digital footprint).
  • Doxing or publishing private information obtained through OSINT.
  • Using the agent to probe systems or services you are not authorized to access.

The legal boundary is straightforward: if the information is on a public website and accessible without authentication, collecting it is OSINT and generally lawful. If you need to log in, bypass a paywall, or circumvent a technical restriction to access it, that is no longer OSINT.

The ethical boundary is stricter than the legal one. Just because you can track someone’s public statements does not mean you should. Use the agent responsibly, and if you are uncertain about a specific use case, consult legal counsel familiar with the laws in your jurisdiction.

Sources

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