Agent Income Lab

Build Your Own AI Research Agent with Python, Claude API and Ready-to-Use Business Research Templates

What if you could build an AI agent that helps businesses research competitors, evaluate suppliers, analyze markets, and prepare professional research reports?

And what if you could turn those technical capabilities into a service that businesses are willing to pay for?

AI-powered business research is an opportunity for developers, consultants, and entrepreneurs interested in creating practical AI agents.

Businesses regularly need reliable information about their competitors, technologies, suppliers, and changing markets. Collecting and organizing that information manually can be time-consuming.

AI models such as Claude can help interpret source material, extract relevant findings, organize comparisons, and prepare structured reports.

However, professional research requires more than asking an AI model to generate an answer.

Research findings need trustworthy sources, accurate citations, evidence verification, and human review.

That’s why we created the Free Claude Business Research Agent Starter Kit.

This downloadable toolkit gives you a practical starting point for building your own AI-assisted research application using Python and the Claude API.

It includes working offline demonstration code, fictional competitor data, citation validation tools, automated tests, and professional Excel and Word templates.

Whether you want to learn AI agent development, start an AI research side hustle, offer business intelligence services, or explore an AI research SaaS product, this kit helps you get started.

Download Your Free Claude Business Research Agent Starter Kit

The complete starter kit is available as a ZIP package containing 15 files.

Inside the download:

• Python business research agent project.
• Optional Claude API integration.
• Fictional competitor research data.
• Structured evidence registry.
• Citation and quotation validation.
• Six automated pytest tests.
• Excel research evidence and quality workbook.
• Client research brief template.
• Research verification checklist.
• Professional research report template.
• Step-by-step README instructions.

Download the Free Claude Business Research Agent Starter Kit →

The offline demonstration does not require an API key. Live Claude execution requires appropriate Anthropic API access and may incur usage charges.

What’s Included in the Starter Kit?

1. Python Business Research Agent

The centerpiece of the download is a Python research application designed to demonstrate how AI-assisted business research can be organized.

The project includes a controlled offline demonstration and an optional integration with the Claude API.

The offline mode lets you explore the research workflow without connecting to a live AI model.

The live integration allows developers to experiment with Claude using their own API credentials and an available model.

The implementation demonstrates how research evidence can be collected into a structured registry, analyzed, and transformed into report drafts.

What you can learn:

• How to structure business research tasks.
• How to organize evidence before AI analysis.
• How to work with the Claude API.
• How to validate research references.
• How to prepare structured research outputs.
• How to separate AI-generated drafts from verified findings.

The project is educational starter code rather than a production-ready intelligence platform.

2. Fictional Competitor Research Dataset

One of the easiest ways to learn research automation is to work with a controlled dataset.

The starter kit includes fictional competitor profiles that demonstrate how business research information can be organized.

You can experiment with competitor comparisons without relying on changing websites or confidential customer information.

The sample data helps illustrate how a research system can record observations about companies, their services, and their positioning.

Why this matters: Using known demonstration data makes it easier to test whether a research workflow behaves as expected before introducing real sources.

3. Evidence Registry and Source Inventory

Professional research depends on knowing where information came from.

The starter kit includes evidence structures and a source inventory template to help organize research material.

A source record can identify the source, associated organization, evidence content, and relevant metadata.

In a real research service, you would also record original URLs, collection dates, and verification status.

What you can do with an evidence registry:

• Organize research sources.
• Maintain source identifiers.
• Trace findings back to supporting material.
• Identify missing information.
• Prepare evidence for review.
• Support report quality checks.

A structured evidence registry is one of the foundations of a trustworthy AI research application.

4. Citation Validation Tools

An AI-generated answer can contain references that look convincing but do not support the underlying claims.

For commercial research, that is a serious problem.

The starter kit includes Python validation logic for checking source identifiers and exact supporting quotations.

This helps detect certain citation problems before a report reaches the customer.

However, there is an important distinction.

A valid source reference does not automatically prove that a claim is correct.

A citation checker can establish that a referenced source exists and that a quoted passage matches the stored evidence.

It cannot automatically guarantee that the entire conclusion is justified.

Human verification remains essential.

5. Six Automated Python Tests

The project includes automated tests using pytest.

These tests cover important aspects of the offline workflow, including valid evidence handling and rejection of selected invalid references or quotations.

Automated testing helps developers understand how a research application should behave when it receives unexpected data.

You can extend the tests as you add new capabilities.

For example, a more advanced application could include tests for duplicate source records, missing metadata, conflicting findings, unsupported claims, and invalid report formats.

6. Research Evidence and Quality Workbook — Excel

The kit includes an editable Excel workbook for managing research quality.

It provides a structured way to organize research sources, track findings, review evidence, and summarize quality measurements.

You can use the workbook to support research assignments for prospective customers.

It also provides a starting point for measuring the consistency of your research process.

Potential metrics include citation coverage, evidence verification, and report completeness.

Use it to: Organize source records, review findings, track quality, and prepare client research projects.

7. Client Research Brief — Word

Before starting a business research project, you need to understand what the customer wants to know.

A client may request a competitor analysis, but that description alone is rarely sufficient.

Which competitors?

Which country?

Which services?

What information matters?

How recent must the sources be?

The Client Research Brief helps define the assignment before work begins.

It includes space for research objectives, questions, scope, target organizations, approved sources, and acceptance criteria.

Use it to: Conduct client discovery and establish a clear research assignment.

8. Research Quality and Verification Checklist — Word

The included quality checklist helps you review a research report before delivering it.

It encourages attention to source authenticity, evidence support, missing information, limitations, and approval.

This is especially important when AI is used to generate analysis or report drafts.

A reliable research service should distinguish between verified facts, incomplete information, and analyst interpretation.

Use it to: Reduce unsupported statements and establish a repeatable review process.

9. Professional Client Research Report Template — Word

The kit also includes an editable business research report template.

It provides a structure for presenting findings professionally.

Sections include:

• Executive summary.
• Research objectives.
• Methodology.
• Competitor or supplier comparison.
• Findings and observations.
• Information gaps.
• Recommendations.
• References.

You can customize the template with your business branding and project information.

Use it to: Prepare consistent client-facing research deliverables.

How to Run the Python Research Agent

After downloading and extracting the ZIP file, open a terminal in the project directory.

You’ll need a suitable Python installation.

Step 1: Create a Virtual Environment

python -m venv .venv

Activate the environment using the appropriate command for your operating system.

Step 2: Install the Development Requirements

python -m pip install -r requirements-dev.txt

Step 3: Run the Automated Tests

python -m pytest -q

The included offline tests help verify that the example research workflow behaves as expected.

Step 4: Run the Offline Demonstration

python -m research_agent.cli --mode offline

The demonstration generates structured research drafts.

Expected output filenames include:

output/research_draft.json

output/research_draft.md

These files show how research findings can be represented as structured data and a readable report.

Step 5: Explore the Claude API Integration

If you want to experiment with live Claude analysis, follow the project’s README instructions.

The live mode requires installing the additional dependencies and configuring:

ANTHROPIC_API_KEY

CLAUDE_MODEL

You can then use the documented Claude execution mode.

Important: The offline project and its automated tests have been checked. The live Claude API execution has not been verified against an Anthropic account as part of this release.

Five Business Research Services You Could Build

Learning the technology is only the first step.

The more interesting opportunity is developing a service that solves a recurring business problem.

Here are five possibilities.

1. AI Competitor Research Reports

Help businesses compare competitors based on approved, verifiable information.

A report might cover service offerings, market positioning, published capabilities, and major differences.

Potential customers: SaaS companies, IT service providers, consultants, and marketing agencies.

2. AI Supplier Research

Assist businesses in identifying and comparing suppliers.

Research criteria might include published product categories, supported regions, services, certifications, and available company information.

Potential customers: Procurement teams, wholesalers, and technical service businesses.

3. Market Landscape Research

Prepare structured overviews of a particular industry or technology market.

A report might identify relevant market participants, product categories, important developments, and outstanding information gaps.

Potential customers: Entrepreneurs, startups, consultants, and B2B organizations.

4. Technology Comparison Reports

Help organizations compare software products, AI platforms, or technology services.

The value comes from an agreed evaluation methodology and reliable evidence.

Potential customers: IT consultants, software buyers, and professional services firms.

5. Recurring Competitor Monitoring

Offer monthly or quarterly updates on approved competitors and relevant business developments.

This is potentially attractive because some customers need research continuously rather than once.

Potential customers: SaaS businesses, consultancies, and marketing teams.

Each opportunity requires market validation, reliable sources, and an appropriate commercial agreement.

How Much Could You Charge for AI Research Services?

Pricing depends on research complexity, verification effort, report depth, and customer requirements.

The following prices are illustrative examples for testing a commercial offer.

These examples are not verified market averages.

A project requiring extensive source verification or specialized industry expertise may cost substantially more.

The starter kit’s research brief, evidence workbook, and report template can help you define a repeatable service.

How to Turn the Starter Kit into a Side Hustle

You don’t need to build an advanced SaaS platform immediately.

Start with a small research offer.

First, choose an industry you understand. For example, IT services, business software, or AI automation platforms.

Next, identify one recurring research problem. Competitor comparisons or supplier evaluations may be suitable.

Then, create a sample report. Use genuine permitted sources, verify important claims, and demonstrate your research methodology.

Prepare your service package. Define the research scope, deliverables, pricing, and review requirements.

Finally, validate customer demand. Offer a limited paid project to an appropriate business.

Once you’ve completed several projects, you may discover opportunities to standardize parts of the workflow or offer ongoing monitoring.

The goal is to establish that customers value your research before investing heavily in a full SaaS application.

Why Source Verification Matters

AI models can generate useful summaries and comparisons, but they can also make mistakes.

A professional research business must distinguish between source collection, AI analysis, and factual verification.

For example, suppose an AI model claims that a competitor recently launched a new service.

Before including the statement in a paid report, you should identify the relevant source and confirm that it supports the claim.

If the information cannot be verified, the report should clearly state that limitation.

The included citation validation code and research quality checklist help you build this discipline into your workflow.

Trustworthy business research is not measured by how quickly AI generates a report. It is measured by whether the findings are useful, traceable, and supported by evidence.

Frequently Asked Questions

Is the Claude Business Research Agent Starter Kit free?

Yes. The kit is a free educational resource from AgentIncomeLab.com.

Does it include Python source code?

Yes. The ZIP contains a runnable Python research project with an offline demonstration and optional Claude API integration.

Do I need an Anthropic API key?

Not for the offline demonstration. Live Claude execution requires appropriate API access.

Can I use the starter kit on Windows?

Yes, the Python project can be used on Windows with a suitable Python installation. The same general approach applies to macOS and Linux.

Does the kit include real competitor research?

No. It includes fictional research data intended for development and testing.

Does the project support citation validation?

Yes. It includes checks for source identifiers and exact supporting quotations. Human review is still required to establish factual support.

Can I customize the Python code?

Yes. The project is intended as a starting point that developers can study and extend, subject to the included project terms and third-party licenses.

Can I use the Excel and Word templates for clients?

They are designed to be customized for research projects. Review the material and applicable requirements before using it commercially.

Can I build a business around AI research?

Potentially. Research reports, supplier comparisons, and competitor monitoring may offer commercial opportunities when customers value the information and are willing to pay.

Is this a complete SaaS application?

No. It is a research agent starter project, not a production multi-tenant SaaS platform.

Can I add live web search?

Yes, through appropriately authorized research and retrieval tools. You must handle source metadata, costs, permissions, and accuracy checks.

Does the kit guarantee accurate research reports?

No. AI analysis and automated citation checks do not eliminate errors. Material findings require independent verification.

Download Your Free Claude Business Research Agent Starter Kit

If you want to learn how to build AI-powered business research applications, this kit provides a practical starting point.

You can experiment with Python, explore Claude API integration, organize research evidence, test citation validation, and prepare professional reports.

You can also use the included business templates to investigate whether research automation could become a freelance service, AI consulting offer, or specialized software product.

Start by building a research workflow you can understand, test, and verify. Then explore how that capability could solve a problem customers are willing to pay for.

Download the Free Claude Business Research Agent Starter Kit →

Free download from AgentIncomeLab.com. Includes Python source code, fictional data, automated tests, Excel templates, and Word documents. Anthropic API usage may incur charges.

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Official Resources

• Anthropic — Claude API Documentation
• Anthropic — Python SDK
• Anthropic — Claude Agent SDK
• Anthropic — Web Search Tool
• Anthropic — API Pricing
• Python — Official Documentation

Editorial disclosure: AgentIncomeLab.com is an independent educational publication and is not affiliated with or endorsed by Anthropic. The starter project is provided for educational purposes. Business models, pricing examples, and revenue opportunities are illustrative and do not guarantee financial results. Research findings should be independently verified before commercial use.