⚡ Digital Labour — 24 AI Agents for Business Automation

Your entire back-office, automated. Run any of 24 specialized AI agents through plain English. Sales outreach, lead generation, content repurposing, SEO, ad copy, bookkeeping, proposals, market research, tech docs — all with built-in QA verification.

Quick Start

Set your API URL (or use the default production endpoint):

export DIGITAL_LABOUR_API_URL="https://bitrage-labour-api-production.up.railway.app"

Test the connection:

python3 {baseDir}/scripts/dl-api.py health

Run an agent:

python3 {baseDir}/scripts/dl-api.py run support_ticket '{"ticket_text": "My order has not arrived after 2 weeks"}'

Available Agents (24 Total)

Revenue & Sales (5 agents)

Agent	Command	What it does
sales_outreach	run sales_outreach '{"company":"Stripe","role":"Head of Sales"}'	Company research + 3-email outreach sequence
lead_gen	run lead_gen '{"industry":"fintech","region":"North America"}'	Generate qualified lead lists for any industry
email_marketing	run email_marketing '{"product":"SaaS CRM","audience":"small business owners"}'	Full email campaign with subject lines + body copy
proposal_writer	run proposal_writer '{"project":"Website redesign","client_name":"Acme Corp"}'	Professional project proposals with pricing
ad_copy	run ad_copy '{"product":"AI writing tool","platform":"google"}'	Platform-optimized ad copy (Google/Facebook/Instagram)

Content & Marketing (4 agents)

Agent	Command	What it does
content_repurpose	run content_repurpose '{"content":"<blog post text>"}'	Repurpose content into tweets, LinkedIn, newsletters
seo_content	run seo_content '{"keyword":"AI automation","content_type":"blog"}'	SEO-optimized content (blog/landing/pillar pages)
social_media	run social_media '{"topic":"AI trends","platform":"linkedin","cta_goal":"drive signups"}'	Platform-native social posts with CTAs
press_release	run press_release '{"announcement":"Product launch","company":"Bitrage"}'	PR-ready press releases

Operations & Data (4 agents)

Agent	Command	What it does
data_entry	run data_entry '{"source_data":"<raw data>","output_format":"CSV"}'	Structure and clean raw data
web_scraper	run web_scraper '{"source_url":"https://example.com","extraction_target":"pricing"}'	Extract structured data from web pages
crm_ops	run crm_ops '{"contact_data":"<contact info>","action":"segment"}'	CRM updates, segmentation, and reporting
bookkeeping	run bookkeeping '{"transactions":"<transaction data>","period":"monthly"}'	Transaction categorization and financial reports

Documents & Research (4 agents)

Agent	Command	What it does
doc_extract	run doc_extract '{"document_text":"<doc text>","doc_type":"invoice"}'	Extract structured data from invoices, contracts, resumes
market_research	run market_research '{"topic":"electric vehicles","depth":"detailed"}'	Market analysis at overview/detailed/comprehensive depth
business_plan	run business_plan '{"business_idea":"AI tutoring app","market":"K-12 education"}'	Full business plans with financial projections
tech_docs	run tech_docs '{"code_or_api":"<code or API spec>","doc_type":"api"}'	API docs, READMEs, and tutorials

Professional Services (3 agents)

Agent	Command	What it does
support_ticket	run support_ticket '{"ticket_text":"<customer issue>"}'	Categorize, prioritize, draft reply for support tickets
product_desc	run product_desc '{"product_specs":"<specs>","tone":"luxury"}'	Product descriptions in any tone
resume_writer	run resume_writer '{"career_data":"<career history>","target_industry":"tech"}'	ATS-optimized resumes for any industry

Management Layer (4 agents)

Agent	Command	What it does
context_manager	Internal orchestration	Maintains context across multi-agent pipelines
qa_manager	Internal orchestration	Quality assurance on every agent output
production_manager	Internal orchestration	Workflow scheduling and resource allocation
automation_manager	Internal orchestration	Autonomous task routing and retry logic

Helper Script

scripts/dl-api.py — Python script (stdlib only) for all API operations.

Commands: | Command | Description | |---------|-------------| | health | Check API health status | | agents | List all available agents with input schemas | | run <agent> <json_inputs> | Run a specific agent with JSON inputs | | batch <json_file> | Run multiple agents from a JSON batch file |

Examples:

# Check health
python3 {baseDir}/scripts/dl-api.py health

# List all agents
python3 {baseDir}/scripts/dl-api.py agents

# Generate sales outreach
python3 {baseDir}/scripts/dl-api.py run sales_outreach '{"company":"Tesla","role":"VP Engineering"}'

# Write a business plan
python3 {baseDir}/scripts/dl-api.py run business_plan '{"business_idea":"AI-powered pet care app","market":"pet owners 25-45"}'

# Generate SEO content
python3 {baseDir}/scripts/dl-api.py run seo_content '{"keyword":"remote work tools 2026","content_type":"pillar"}'

# Run a batch of tasks
python3 {baseDir}/scripts/dl-api.py batch {baseDir}/examples/batch.json

Batch Processing

Create a JSON file with multiple tasks:

[
  {"agent": "sales_outreach", "inputs": {"company": "Stripe", "role": "CTO"}},
  {"agent": "ad_copy", "inputs": {"product": "AI CRM", "platform": "facebook"}},
  {"agent": "seo_content", "inputs": {"keyword": "business automation", "content_type": "blog"}}
]

Run them all:

python3 {baseDir}/scripts/dl-api.py batch tasks.json

Multi-Agent Workflows

Chain agents together for complex operations:

Lead-to-Close Pipeline: 1. lead_gen → find prospects in target industry 2. market_research → understand their pain points 3. sales_outreach → personalized outreach sequence 4. proposal_writer → ready proposal when they respond

Content Engine: 1. market_research → trending topics in your niche 2. seo_content → long-form SEO blog post 3. content_repurpose → tweets, LinkedIn, newsletter from that post 4. social_media → platform-native posts with CTAs 5. ad_copy → paid promotion copy

Client Onboarding: 1. doc_extract → pull data from client documents 2. data_entry → structure into your system format 3. bookkeeping → set up financial tracking 4. crm_ops → create CRM records

API Details

• Base URL: https://bitrage-labour-api-production.up.railway.app
• Universal Endpoint: POST /v1/run
• Agent List: GET /agents
• Health Check: GET /health
• Docs: GET /docs
• LLM Providers: OpenAI (GPT-4o), Anthropic (Claude), Google (Gemini), xAI (Grok)
• QA: Every output passes through QA verification before returning

Environment Variables

Variable	Required	Default	Description
DIGITAL_LABOUR_API_URL	Yes	https://bitrage-labour-api-production.up.railway.app	API base URL
DIGITAL_LABOUR_API_KEY	No	(none)	Optional API key for authenticated access

Important Notes

• Each agent call takes 3-15 seconds (real LLM inference, not cached)
• All outputs include QA verification status
• The provider field is optional in all agent inputs — omit to use the server default
• Management agents (context_manager, qa_manager, etc.) are internal and run automatically during pipelines
• Batch mode processes tasks sequentially to respect rate limits
• All agent outputs are structured JSON with consistent schema