A few examples of the kind of work CDB Logic takes on: internal tools, workflow automation, discovery products, and systems that make repeated work easier to run.
Internal operations
Sales needed a faster way to build consistent proposals without recreating pricing logic by hand.
A guided quoting tool with structured inputs, pricing flow, proposal output, and cleaner handoff points.
Less manual assembly, more consistent proposals, and a clearer path from quote to next action.
Fulfillment workflow
Order details were spread across messages, notes, and repeated entry steps.
A focused order entry interface designed around the information operations actually needs to move work forward.
Cleaner capture, fewer back-and-forth questions, and a more reliable operational record.
AI systems
Recurring content work needed structure, repeatability, and review before publishing.
A generation pipeline that creates drafts, images, metadata, and publishing-ready assets with human oversight.
A repeatable system for turning topics into posts without starting from a blank page every time.
Discovery tools
People needed a faster way to compare practical local service options without digging through cluttered results.
A lightweight discovery interface shaped around neighborhood-level search and clear comparison points.
A more direct path from need to useful local options.
Trust signals
The work is strongest when the system supports a real workflow, gives people clarity, and keeps important business logic easy to reason about.
Built for real operational workflows
Human review where AI needs guardrails
Private/internal tools supported
Fast prototypes with production paths
Clear handoffs and audit-friendly flows
Business logic kept visible
Have a similar workflow?
Describe the messy version. That is usually where the useful system starts.