Klaus
· by Robbie

OpenClaw for Company Research and Competitive Intelligence

Mikayla Mooney, a partner at Ag Startup Engine, uses Klaus to screen deal flow. Her agent pulls company profiles, checks funding history, and compiles a briefing before she opens her laptop. She told us Klaus has helped her “go deeper on diligence, quickly produce research on companies, and stay on top of deal flow.”

Research is the use case where an AI agent saves the most human time. The work is inherently repetitive: checking the same sources, compiling the same types of data, every day or every week. An agent does this without being asked twice.

What Does Company Research Look Like with an Agent?

Company research with an OpenClaw agent means connecting structured data APIs to a conversational interface that runs research on a schedule. Instead of opening five tabs and copying data into a spreadsheet, you describe what you need and the agent pulls it together.

Three research workflows we see across Klaus customers:

Deal flow screening. An investor or partner describes their criteria (“Series B fintech in Europe, 50-200 employees”) and the agent searches for matches, pulls company profiles, checks recent funding rounds, and delivers a one-page summary for each company. This is what Mikayla at Ag Startup Engine uses daily.

Competitive monitoring. A founder tracks 5-10 competitors weekly. The agent checks for pricing changes, new product announcements, leadership changes, and hiring patterns, then flags anything that changed since the last check.

Board meeting prep. Instead of spending a Sunday afternoon pulling slides together, the agent compiles market data, competitor updates, and customer metrics into a structured briefing document the night before the meeting. You review and edit in 20 minutes.

The Research Stack

These are the tools that power these workflows:

ToolWhat it doesResearch role
ExaAI-native semantic search across 70M+ companiesFinds companies, news, and research papers by meaning, not just keywords (docs.openclaw.ai)
ApolloPeople and company dataEnriches company profiles with contacts, org structure, and tech stack (GitHub)
CoresignalPublic web data across 4.5B+ recordsTracks headcount growth, key hires, and departmental changes over time (Coresignal)
CI skillCompetitive intelligence frameworkLandscape mapping, battle cards, and automated alerts (GitHub)

On Klaus, Exa, Apollo, and Coresignal are available via Orthogonal with pre-loaded credits. On self-hosted OpenClaw, you bring your own API keys.

Worth noting: 82% of executives use competitive intelligence tools weekly, but 55% cite data overload as their primary challenge. The point of an agent is not more data. It is filtered, structured data delivered without the manual work.

How to Set Up a Research Workflow

The walkthrough below sets up a weekly competitive briefing. The same pattern works for deal screening, board prep, or any recurring research task.

Step 1: Install the Research Stack

On Klaus, Exa, Apollo, and Coresignal are all available through Orthogonal out of the box. No API keys to configure, no skills to install. Your Starter plan ($19/mo) includes $20 of Orthogonal credits that cover all three.

If you’re self-hosting, install the skills from ClawHub and bring your own API keys:

clawhub install exa
clawhub install competitive-intelligence-market-research
clawhub install apollo

Exa requires an EXA_API_KEY set in your environment or via openclaw configure --section web (Exa docs). Apollo requires an APOLLO_API_KEY in config/apollo.env (Apollo skill).

Step 2: Define What You’re Tracking

Tell the agent what to monitor in natural language:

“Track these 5 competitors. Check for pricing changes, new product announcements, leadership changes, and funding rounds. Compile a weekly briefing every Monday morning.”

Exa’s neural search mode finds relevant pages by meaning, not exact keyword matches. A query like “Series B fintech companies in Singapore with 50-200 employees” returns structured results because Exa indexes 70M+ companies with proprietary embeddings.

Apollo enriches each company with org data, contacts, and tech stack via apollo-enrich-website.sh (Apollo skill). Coresignal adds hiring signal context: if a competitor’s engineering team grew 40% in six months, that tells you something about their roadmap. Coresignal’s Company Data API covers 500+ fields with an average response time of 176ms.

Step 3: Schedule and Deliver

Set up the agent to run on a schedule using cron or a conversation trigger. Output options include:

  • A Slack channel (the CI skill supports automated Slack and Discord alerts on detected changes)
  • An email digest via AgentMail
  • A workspace file your team can review
  • A Google Doc updated weekly

A completed briefing looks like a structured document with a section per competitor, change flags (“pricing updated,” “new VP of Engineering hired,” “Series C announced”), and source links for everything. The agent highlights what changed since the last run, not just what exists.

Research Use Cases We See Across Customers

Deal Flow and Due Diligence

Mikayla Mooney at Ag Startup Engine runs this workflow for every inbound deal. Her agent screens companies by pulling Coresignal profiles, checking Exa for recent news coverage, and enriching founder profiles via Apollo. The output is a one-page summary before her first call with the company.

This pattern is not unique to venture capital. StackAI’s enterprise customers use Exa-powered agents for “mission-critical operations like due diligence, competitive intelligence, RFP response drafting, and market research”. Any role that requires regular company research benefits from this setup: business development, partnerships, M&A, procurement.

Weekly Competitive Monitoring

This is the most common research workflow we see on Klaus. A founder or product lead tracks a set of competitors and gets a weekly digest.

The agent detects changes and flags them: “Competitor X added a new enterprise tier” or “Competitor Y posted 12 engineering jobs this week after posting 2 last month.” The competitive intelligence skill reports an 85% reduction in manual research time with continuous monitoring and smart change detection.

What makes this more useful than Google Alerts: the agent cross-references multiple data sources (Exa for news, Coresignal for hiring, Apollo for org changes) and compiles them into a single structured output. Google Alerts sends you individual notifications. The agent sends you a brief.

Board Meeting and Investor Prep

The night before a board meeting, the agent compiles market data, competitor landscape updates, and relevant customer metrics into a structured document. Exa pulls market news and industry trends. Coresignal tracks competitor headcount and key hires.

The output is a board-ready draft you review and edit rather than build from scratch. We have seen customers cut their board prep from a full afternoon to under an hour.

The competitive intelligence tools market is projected to reach $1.28B by 2033, growing at 12.6% annually. Companies with dedicated CI see 5.2x average ROI on their CI investment, peaking at 7x when AI is integrated. An OpenClaw agent with these tools is not a replacement for strategic thinking. It is a replacement for the data collection that precedes it.

Frequently Asked Questions

What does the research stack cost?

On Klaus Starter ($19/mo), you get $20 of Orthogonal credits that cover Exa, Apollo, and Coresignal usage. Self-hosted: bring your own API keys. Exa has a free tier, and Apollo’s free tier includes 300 credits per month. The competitive intelligence skill itself is free on Clawhub.

How is this different from ChatGPT or Perplexity?

ChatGPT and Perplexity answer questions from training data or web search results. An OpenClaw agent runs a pipeline: it searches specific sources via Exa, enriches data via Apollo and Coresignal APIs, tracks changes over time, and delivers structured output on a schedule. The difference is automation and persistence. The agent runs the same research workflow every week without being asked.

Can the agent access paywalled or private data?

No. Exa, Apollo, and Coresignal access publicly available data. For internal data, you would connect the agent to your own databases or APIs. The agent cannot bypass paywalls or access login-protected content unless you configure specific credentials.

How accurate is agent-compiled research?

The agent surfaces data from structured APIs (Apollo, Coresignal) and web search (Exa). The data is as accurate as its sources. For critical decisions, verify key claims before acting on them. The briefing gives you a starting point, not a final verdict. If you act on unverified data from any tool, you risk the same mistake as trusting a search snippet without reading the source.

Key Takeaways

  • Research is repetitive work: checking the same sources and compiling the same data formats on a schedule. An agent automates the entire pipeline.
  • The research stack consists of Exa (semantic search), Apollo (company and people data), Coresignal (hiring and growth signals), and the competitive intelligence skill (monitoring and alerts).
  • Common workflows include deal flow screening, weekly competitive monitoring, and board meeting prep.
  • On Klaus, the entire stack comes pre-configured via Orthogonal. On self-hosted OpenClaw, you install skills and bring your own API keys.
  • Start with one workflow (weekly competitive briefing or deal screening) before expanding to more complex research automation.
  • The agent produces a starting point for research, not the final analysis. Human judgment still makes the decision.

If you want to try this, sign up at klausai.com. Exa, Apollo, and Coresignal are ready on your instance. For the full deep-dive on data-gathering tools, see our web scraping guide. For more customer workflows, see how our customers actually use OpenClaw.

Sources