openbusiness 0.1.0

Evidence-first AI business model analysis and reverse engineering

OpenBusiness

Evidence-first AI business model analysis and reverse engineering for founders, investors, consultants, and strategy teams.

OpenBusiness is an open-source AI agent CLI for business model analysis, competitive research, market research, go-to-market strategy, unit economics, and business model canvas generation. Give it a company name, domain, and optional stock ticker; it collects evidence from the web, runs specialized analyst agents, builds a structured business model canvas, stress-tests assumptions, and labels each claim as verified, inferred, or missing.

It is inspired by TradingAgents, but OpenBusiness is not a bull-vs-bear debate system. Business model analysis needs decomposition, evidence tracking, and assumption pressure-testing, not a buy/sell vote.

Highlights

• Multi-agent business analysis pipeline built with LangGraph.
• Evidence collection through Tavily search, Firecrawl scraping, and SEC EDGAR.
• Business model canvas output with explicit evidence labels: known, inferred, or missing.
• Domain analysis packs for SaaS, public companies, ecommerce, AI infrastructure, consumer apps, and general company research.
• Audience templates for standard analysis, investor memos, founder copycat studies, and competitor maps.
• Reproducible run artifacts with stage outputs, source extraction, and run metadata.
• Bilingual report generation with --language en and --language zh.
• Provider support for OpenAI, Anthropic, and DeepSeek.
• Local config wizard with hidden API-key input and 0600 config permissions.
• Language-purity warnings when generated reports mix output languages.
• Pure Markdown reports that can be archived, edited, or shared directly.

Use Cases

OpenBusiness is useful when you need a structured first-pass business model research report before deeper diligence:

Audience	Common question	OpenBusiness output
Founders	What can I copy, avoid, or attack in this market?	GTM motion, value proposition, moat, and fatal weakness.
Investors	Is the company robust, plausible, fragile, or speculative?	Evidence-labeled thesis, assumptions, and stress test.
Consultants	How does this company actually make money?	Business model canvas, profit engine, and unit economics.
Product teams	Why do customers switch and stay?	JTBD, adoption friction, switching triggers, and alternatives.
Researchers	What data is missing before making a stronger claim?	Missing-data inventory and validation plan.

Search keywords: AI business model analysis, business model reverse engineering, business model canvas generator, AI market research, AI competitive analysis, go-to-market analysis, startup analysis, unit economics analysis, LangGraph agents, evidence-first research.

What It Produces

OpenBusiness writes a final Markdown report with this shape:

# OpenBusiness Business Model Reverse Engineering Report

**Target:** Notion | **Confidence:** Plausible

## 1. Business Model Canvas

| Key Partners | Key Activities | Value Propositions | Customer Relationships | Customer Segments |
| --- | --- | --- | --- | --- |
| Stripe, AWS, app ecosystem [INFERRED] | Product development, collaboration workflows [VERIFIED:notion.so] | All-in-one workspace [VERIFIED:notion.so] | Self-serve PLG plus enterprise support [INFERRED] | Teams, startups, creators, enterprises [VERIFIED:notion.so] |

## 2. Key Fact Layers

### Verified Facts

- Pricing includes Free, Plus, Business, and Enterprise tiers. [VERIFIED:notion.so/pricing]

### Inferred Assumptions

- Expansion likely depends on team-level workspace adoption. [INFERRED]

### Missing Data

- Actual CAC, gross margin, and cohort retention are not publicly disclosed. [MISSING]

## 3. Assumption Stress Test

## 4. Next Steps

Evidence Discipline

The central product principle is simple: know what is known, infer only when the evidence supports it, and mark the unknown instead of hiding it.

Evidence labels are intentionally visible and treated as part of the report contract:

Label	Meaning
[VERIFIED:url]	The claim is supported by a source.
[INFERRED]	The claim is a reasoned inference from available context.
[MISSING]	The missing data materially affects confidence.

This is a feature, not a formatting detail. OpenBusiness keeps these labels through collection, analysis, synthesis, stress testing, and finalization. Analysis packs and report templates can change the lens of the analysis, but they must not remove or soften the evidence labels.

Quick Start

1. Clone

git clone https://github.com/wanikua/OpenBusiness.git
cd OpenBusiness

2. Install

./install.sh

The installer asks you to choose English or Chinese first, checks Python, creates a virtual environment if needed, installs the package in editable mode, and starts the configuration wizard in the selected language. That first language choice becomes the default terminal UI language and the default report language for openbusiness analyze, unless you explicitly override the report language later.

If you accept the default .venv setup, the installer activates it for the installation session. In every new terminal, activate it again before running openbusiness:

source .venv/bin/activate

If you declined virtual environment creation, skip this activation step and use the Python environment where you installed the package.

3. Configure Or Reconfigure

openbusiness config

The installer normally starts this wizard automatically. Run it manually when you skipped the wizard, changed terminals before completing setup, or need to update keys later.

The setup stores:

Setting	Required	Notes
Interface language	Yes	Set by the installer or openbusiness config --ui-language en.
LLM provider	Yes	openai, anthropic, or deepseek
Report language	Yes	Defaults to the interface language; can be changed with --language.
Provider API key	Yes	OpenAI, Anthropic, or DeepSeek key
Tavily API key	No	Enables live search evidence
Firecrawl API key	No	Enables page scraping evidence

Config is saved to ~/.config/openbusiness/config.toml.

4. Run

source .venv/bin/activate
openbusiness analyze "Notion" --domain notion.so --language en

If your shell prompt already shows the virtual environment is active, you do not need to run source .venv/bin/activate again in the same terminal.

The report is written to output/notion_business_model.md.

CLI

source .venv/bin/activate

openbusiness config
openbusiness config --reset
openbusiness config --language en
openbusiness config --ui-language en
openbusiness show
openbusiness packs
openbusiness templates

openbusiness analyze "Notion" --domain notion.so
openbusiness analyze "Costco" --ticker COST
openbusiness analyze "Vercel" --domain vercel.com --output reports/
openbusiness analyze "Notion" --domain notion.so --language en
openbusiness analyze "Notion" --domain notion.so --language zh
openbusiness analyze "Notion" --domain notion.so --ui-language en --language zh
openbusiness analyze "Notion" --domain notion.so --depth deep
openbusiness analyze "Vercel" --domain vercel.com --pack saas --template investor-memo

Analysis options:

Option	Description
--domain, -d	Official company domain for evidence gathering.
--ticker, -t	Public-company ticker for SEC EDGAR lookup.
--output, -o	Output directory. Defaults to output/.
--language, -l	Report language for this run. Supports en and zh.
--ui-language	Terminal interface language for this run. If --language is omitted, the report follows the resolved interface language by default.
--depth	Research depth. Use standard for faster runs or deep for broader evidence collection.
--pack	Built-in analysis pack id. Run openbusiness packs to list options.
--pack-file	Custom analysis pack TOML file.
--template	Built-in report template id. Run openbusiness templates to list options.
--template-file	Custom report template Markdown file with TOML front matter.

openbusiness analyze does not ask for language choices at startup. The terminal UI language comes from install/config, and the report language follows that UI language unless you explicitly set --language, OPENBUSINESS_OUTPUT_LANGUAGE, or openbusiness config --language.

Environment Variables

Environment variables override local config. They are useful for CI, containers, and temporary provider switches.

export OPENBUSINESS_PROVIDER=deepseek
export OPENBUSINESS_UI_LANGUAGE=en
export OPENBUSINESS_OUTPUT_LANGUAGE=en
export DEEPSEEK_API_KEY=sk-xxx
export DEEPSEEK_BASE_URL=https://api.deepseek.com
export DEEPSEEK_TIMEOUT=60
export DEEPSEEK_MAX_RETRIES=1
export DEEPSEEK_MAX_TOKENS=2048
export TAVILY_API_KEY=tvly-xxx
export FIRECRAWL_API_KEY=fc-xxx

openbusiness analyze "Notion" --domain notion.so

Interface language precedence:

1. openbusiness analyze --ui-language en
2. OPENBUSINESS_UI_LANGUAGE=en
3. ui_language = "en" in local config
4. Default: zh

Report language precedence:

1. openbusiness analyze --language en
2. OPENBUSINESS_OUTPUT_LANGUAGE=en
3. output_language = "en" in local config
4. Resolved interface language

Analysis Packs And Templates

Analysis packs make the pipeline more domain-aware without hard-coding every company into one generic prompt. Built-in packs include:

Pack	Use it for
general	Default company research when the model is unclear or mixed.
saas	Subscription software, PLG, sales-led SaaS, and B2B software.
public-company	Listed companies where filings, segments, and margins matter.
ecommerce	DTC, marketplace, retail commerce, and product businesses.
ai-infra	Developer tools, model platforms, data tooling, and AI infrastructure.
consumer-app	Consumer, prosumer, creator, media, and community products.

Report templates change the reader lens:

Template	Use it for
standard	General OpenBusiness report.
investor-memo	First-pass diligence, business quality, and downside risk.
founder-copycat	What to copy, avoid, attack, or validate as a new entrant.
competitor-map	Alternatives, likely competitive response, and positioning.

Examples:

openbusiness packs
openbusiness templates
openbusiness analyze "Vercel" --domain vercel.com --pack saas --template investor-memo
openbusiness analyze "Costco" --ticker COST --pack public-company

Custom packs are TOML files with id, name, description, evidence_focus, and analyst_focus. Custom templates are Markdown files with TOML front matter. Both are prompt guidance only: they cannot bypass evidence labels or turn missing data into verified facts.

Run Artifacts

Each run keeps the existing portable report path:

output/<company>_business_model.md

It also writes a reproducible artifact folder:

output/<company>/
├── report.<language>.md
├── run.json
├── evidence.json
├── sources.md
└── stages/
    ├── 01_evidence.md
    ├── 02_jtbd.md
    ├── 03_value_prop.md
    ├── 04_gtm.md
    ├── 05_unit_econ.md
    ├── 06_moat.md
    ├── 07_canvas.md
    ├── 08_stress_test.md
    └── 09_final.md

This makes reports easier to debug, compare, and improve. If a conclusion feels too shallow, inspect the stage files to see whether the weakness came from missing evidence, weak inference, or final-report compression.

Bilingual Output

OpenBusiness supports English and Simplified Chinese report generation:

openbusiness analyze "Notion" --domain notion.so --language en
openbusiness analyze "Notion" --domain notion.so --language zh
openbusiness analyze "Notion" --domain notion.so --ui-language en --language zh

Without --language, the report follows the terminal UI language selected during installation or configuration. Use --language when you want the UI and report languages to be different.

The language contract is applied to every analyst node. Final reports also run a language-purity check:

• English reports warn if generated content contains Chinese characters.
• zh reports warn if generated content contains English section headings or English-like prose lines.
• Company names, URLs, tickers, metric abbreviations, API/tool names, model names, and evidence tags are preserved intentionally.

Depth Mode

Use --depth deep when you want a more serious research pass:

openbusiness analyze "Notion" --domain notion.so --language zh --depth deep

standard keeps evidence collection bounded for faster runs. deep lets the evidence collector spend more tool rounds and use broader search depth for customer proof, hiring signals, ecosystem clues, competitor positioning, and negative evidence. All analyst nodes still use the same depth standard: major conclusions must include mechanism, evidence quality, countercase, business implication, and validation data.

Pipeline

Company name + optional domain + optional ticker
  |
  v
Evidence Collector
  |-- Tavily search
  |-- Firecrawl scrape
  |-- SEC EDGAR facts
  v
JTBD Analyst
  v
Value Proposition Analyst
  v
GTM Analyst
  v
Unit Economics Analyst
  v
Moat Analyst
  v
Business Model Synthesizer
  v
Assumption Stress Tester
  v
Finalizer
  v
output/<company>_business_model.md
output/<company>/run.json + stage artifacts

Core design principles:

• Evidence first: source material is collected before analysis.
• Claims stay tagged: verified facts, inferred assumptions, and missing data are never flattened into one confidence level.
• Tools do deterministic work: unit-economics calculations run in Python, not inside model prose.
• The final output is portable Markdown.
• Analysis packs and templates can change the lens, but the evidence-label contract stays fixed.

Providers

Provider	Config key	Notes
OpenAI	OPENAI_API_KEY	Default provider.
Anthropic	ANTHROPIC_API_KEY	Supported through LangChain Anthropic.
DeepSeek	DEEPSEEK_API_KEY	Uses an OpenAI-compatible endpoint.

Optional evidence APIs:

Service	Config key	Purpose
Tavily	TAVILY_API_KEY	Web search evidence.
Firecrawl	FIRECRAWL_API_KEY	Website and page scraping.

If Tavily or Firecrawl is not configured, the pipeline still runs, but more claims will be marked [INFERRED] or [MISSING].

Project Structure

OpenBusiness/
├── install.sh
├── pyproject.toml
├── README.md
├── LICENSE
├── CONTRIBUTING.md
├── llms.txt
├── .env.example
├── docs/
│   ├── PROMOTION.md
│   ├── EXTENDING.md
│   └── assets/
│       ├── openbusiness-terminal-demo.svg
│       └── openbusiness-report-preview.svg
├── .github/
│   └── workflows/
│       └── ci.yml
└── openbusiness/
    ├── cli.py
    ├── language.py
    ├── profiles.py
    ├── resources/
    │   ├── packs/
    │   └── templates/
    ├── agents/
    │   ├── analysts/
    │   └── utils/
    ├── graph/
    ├── llm_clients/
    └── tools/

Development

python -m pip install -e ".[dev]"
python -m ruff check openbusiness
python -m compileall openbusiness
bash -n install.sh
python -m openbusiness.cli packs
python -m openbusiness.cli templates

Supply-chain and release hygiene:

• CI installs from the checked-out package and runs lint, compile, installer syntax, resource smoke tests, and the README English-only check.
• Runtime resources are packaged through pyproject.toml package data instead of fetched dynamically at install time.
• Generated output, local config, API keys, and virtual environments must stay out of commits.
• README and top-level metadata stay English-only for GitHub and package-index readability.

Community

OpenBusiness is meant to be co-built with people who care about better business research. The goal is not only to ship an AI agent demo, but to build a shared open-source workflow for evidence-labeled company analysis.

• Star the repository if OpenBusiness helps your research workflow.
• Open an issue for bugs, missing providers, report-quality problems, or company-analysis examples that expose weak reasoning.
• Share real analysis examples that show where the pipeline is shallow, slow, or missing important evidence.
• Contribute domain packs, report templates, evidence connectors, or better stage prompts when you can show how they improve evidence quality or reasoning depth.
• Read CONTRIBUTING.md before sending a pull request.
• Use docs/EXTENDING.md when adding analysis packs, report templates, or evidence tools.
• Use docs/PROMOTION.md for launch copy, GitHub topic suggestions, and community posting templates.
• llms.txt is available for AI assistants, answer engines, and developer tools that need a compact project summary.

Troubleshooting

./install.sh: Permission denied

chmod +x install.sh
./install.sh

openbusiness: command not found

Activate the virtual environment used during installation:

source .venv/bin/activate

The report is mostly inferred

Configure Tavily and Firecrawl so the evidence collector can gather live source material:

openbusiness config --reset

The report language is mixed

Run with an explicit language override:

openbusiness analyze "Notion" --domain notion.so --language en
openbusiness analyze "Notion" --domain notion.so --language zh

If the warning persists, retry with a model that follows formatting and language constraints more strictly.

License

OpenBusiness is released under the MIT License. See LICENSE for the full license text.