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MWM DatallogTurn local Python scripts into secure automations.

Create new automations or organize existing ones. Run integrations, scrapers, and AI scripts with built-in deployment, scheduling, and observability.

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⚡ Zero Ops

You write the logic, we manage the runtime and infrastructure. No YAML, no headaches.

🐳 Automated Containers

Seamless transition from local to cloud. We build and manage the Docker containers for you.

🛡️ Predictable Pricing

Pre-paid model. Infinite scale with finite budget control. No bill shocks.

Simple as Python. Powerful as Cloud.

Write a standard function, decorate it, and push.

1. Example: from local script to automation ​

A simple example showing how a local Python script becomes an automation.

python
from datallog import automation

# Entry point: receives the input data
@automation()
def process_data(seed):
    items = seed.get("items", [])
    results = []
    # Process items
    for item in items:
        results.append(heavy_computation(item))
    return {"status": "done", "results": results}

2. Example: lead enrichment and qualification automation ​

A single automation to collect, qualify, and send leads to the sales team.

python
from datallog import automation

# A single automation to collect, qualify, and send leads
@automation()
def process_leads(seed):
    leads = get_data_leads(seed)
    
    for lead in leads:
        enrichment = enrich_company_data(lead["email"])
        score = calculate_score(enrichment)
        
        send_email(
            to="sales@company.com",
            subject="New qualified lead",
            body=f"{lead['email']} — score {score}"
        )
        
    return {"status": "done"}