Software and SaaS development
Digital products that solve, scale and evolve.
Insights
Guides, analysis and lessons on product, artificial intelligence, growth, communications and cloud.
Editorial themes
Digital products that solve, scale and evolve.
AI systems for real-world processes.
Demand, catalogue, partners and conversion.
Every conversation in the right channel.
Available, observable and ready services.
Set rules for detecting duplicate customers, deciding which records to merge, and protecting useful data through confidence levels, human review, and traceability.
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Learn how to assess whether you can replace a SaaS solution without losing data or disrupting workflows by reviewing exports, dependencies, exit tests, and responsibilities.
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A practical framework for choosing, preserving, and reconciling identifiers across CRM, ERP, ecommerce, and custom applications without confusing entities.
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Choosing when to reserve inventory prevents overselling and inventory lockups. This framework helps define timing, expiration periods, priorities, and operational controls.
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Decide which systems should create, read, and update data to choose synchronization that is secure, manageable, and aligned with each process.
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A spreadsheet can support useful processes for years. This framework helps identify when its flexibility becomes an operational risk.
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A shared state model prevents discrepancies between applications, clarifies ownership, and helps detect stalled processes before they affect customers.
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A practical framework for assigning autonomy to automations based on impact, reversibility, uncertainty, context, and the ability to correct errors.
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Learn how to prioritize errors in digital processes using operational criteria to block, alert, or correct them without unnecessarily slowing the business.
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A practical framework for deciding which data travels in an event, which data is retrieved later, and how to avoid dependencies, stale data, and security risks.
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A practical framework for deciding which internal processes require an SLA and which need reviewable operational targets, without inflating costs.
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A practical framework for assigning authority to each data point, reducing conflicts between systems, and designing traceable, sustainable integrations.
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