Backend services
Implement application rules and integrate data from existing systems.
Python services, APIs and automation for business products, with explicit data contracts, background work and operational handover.
for row in catalogue:
result = validate(row)
if result.valid:
queue.upsert(row)
else:
report.add(result.errors)Capability Example
A supplier uploads a CSV with valid rows, duplicates and missing prices.
Illustrative data. Nothing is sent to an external system.
1row 1: valid
2row 2: duplicate SKU
3row 3: price missing
Check the file schema and collect row-level errors.
1valid row processed
2invalid rows isolated
3job_id: import-17
Upsert valid rows in bounded batches with a resumable job ID.
1accepted: row 1
2corrections: rows 2 and 3
3retry uses the same import ID
Return accepted, rejected and unchanged record counts.
An import result with actionable row errors and a repeatable retry path.
Implement application rules and integrate data from existing systems.
Validate files, transform records and schedule repeatable operations.
Maintain frameworks, improve test coverage and untangle slow or fragile jobs.
Separate interactive API latency from long-running processing needs.
Define validation and conflict rules before allowing imported data to overwrite records.
Choose from the product's needs: administration, authentication, API contracts and existing code matter more than framework preference.
Yes. It can expose an API for React, Vue, Angular or mobile clients without replacing those interfaces.
Share the data flow, existing integrations and examples of successful and failed inputs.
What our clients value about working with Daphnis Labs.
The team at Daphnis Labs redefined what’s possible for Urbanface. They delivered a bespoke, animation-heavy website that remains incredibly quick and functional. The…
We wanted a unique, 'one-of-a-kind' feel for Glareen, and Daphnis Labs delivered an ecosystem that is both beautiful and technically superior. Their expertise in…
The level of technical depth Daphnis Labs brought to our Game project is unparalleled. While the front-end reel games are visually stunning and highly engaging, the…
Practical perspectives on AI, product engineering, commerce and modern software delivery.

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Check Sonnet 5.5's token costs, thinking settings and conversation requirements, then evaluate coding changes against a concrete merchant-sorting fixture.
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Check Gemini 4 Argon's access rules, shared token budget and launch pricing, then use a controlled supplier-data evaluation to plan an API migration.
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