AI-assisted software engineering for Python automation, API integration, and reliable business workflows. Clearly scoped. Thoroughly tested. Verifiable by design.
Switch between four working domains. The preview uses explicitly synthetic records; the detailed demos let you change real inputs and inspect every recalculated result.
Change CSV records and see validated metrics update.
Explore four engineering prototypes built around the messier parts of real operations—bad data, duplicate records, unreliable workflows, and privacy boundaries.
All interactive demos ↗Find bad rows before they become bad decisions. Validate uploads, calculate KPIs, and export exceptions.
Open interactive demo ↗Qualify inbound demand with explainable rules, duplicate detection and a human approval checkpoint.
Open interactive demo ↗Make CRM stages observable. Replay automated actions safely and inspect the complete activity trail.
Open interactive demo ↗Search local example documents and explore an explicit data-sharing approval boundary.
Open interactive demo ↗Transparent by design: all demos use synthetic inputs and local browser behavior. They demonstrate engineering approach, not past client engagements or live third-party integrations.
Verification & limits ↗We take on tightly scoped work with a clear definition of success. No vague promises. No one-size-fits-all transformation pitch.
Find evidence of failure before commissioning a fix. Receive prioritized findings and reproducible checks.
Investigate one reproducible API, webhook, or workflow failure.
Make two systems exchange data with dependable error handling.
Turn a repeatable manual process into a testable workflow.
Indicative starting prices; final price and delivery terms depend on a mutually agreed scope.
DEEPLINK uses AI-assisted engineering for analysis, implementation, test development, and documentation. Every project still requires a defined scope and independently checkable acceptance criteria.
Agree on systems, inputs, expected behavior, exclusions, and data access before development.
Use Python and approved AI tools to implement the specific integration, audit, or automation.
Record reproducible tests, retries, duplicate handling, limitations, and the final acceptance outcome.
Privacy boundary: confidential client material is not submitted to external AI tools without authorization. Written-first collaboration is preferred; production actions require explicit approval.
Trust comes from observable behavior, accountable scope, and transparent limits—before a production environment is touched.
Clarify inputs, expected outputs, access boundaries, and exclusions.
Implement the smallest reliable workflow with explicit failure handling.
Test repeat actions, failure cases, and acceptance conditions.
Deliver operating notes, known limitations, and an auditable result.
Explore alternate visual directions and apply a new design site-wide in one click.
Open the design lab ↗Unlike the browser-only demonstrations, DEEPLINK's internal inquiry system uses an actual AWS serverless backend. This is not a paid client case study.
Our internal intake system stores a reference before asynchronous email processing, retains failed requests for review, and records delivery attempts. During internal QA, an SES permissions issue was diagnosed and corrected, and a subsequent test inquiry was stored and received by email.
SENT statusTell us where your workflow breaks. We’ll scope what can be verified and delivered.
Request a scope review ↗