First product release
Turn a validated problem into an end-to-end experience people can use.
Build the smallest usable product that tests a real customer workflow, with enough operational support to learn from its first release.
Capability Example
A founder wants to learn whether customers will request a specialist appointment.
Illustrative data. Nothing is sent to an external system.
Limit the release to discovery, request and operator confirmation.
Implement the customer journey and a simple operations queue.
Track completed requests and interview users about abandoned steps.
A usable booking experiment with evidence for deciding what to build next.
Turn a validated problem into an end-to-end experience people can use.
Replace a proven manual service with a focused software workflow.
Test a bounded capability before extending an established platform.
Agree the question the release must answer and which features do not help answer it.
Integrations and product complexity determine milestones; a fixed sprint is a separate engagement.
Not necessarily. We distinguish exploratory prototypes from a usable release and decide which foundations need to survive future work.
This service covers discovery-to-release MVP delivery with scope-driven milestones. The sprint is a bounded engagement for work that fits its agreed capacity.
Bring the user problem, any validation evidence and the one journey the first release must complete.
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.

Separate Kimi's API and coding-plan limits, budget cache writes correctly, and evaluate a repository refactor against behavior that must survive the change.
Read Blog
Budget beyond Mercury 3's launch discount, check its streaming and reasoning defaults, and measure how quickly a support agent produces a correct, usable answer.
Read Blog
Separate the model's context from each provider's limits, calculate a coding-pilot budget, and test a mobile layout repair before committing to self-hosted hardware.
Read Blog
Compare recorded and realtime transcription costs, identify launch-documentation conflicts, and test whether a corrected collection request survives the trip from audio to an operations draft.
Read Blog
Check the released model's token rates and API compatibility, calculate a realistic pilot budget, and evaluate image evidence against changing inventory records.
Read Blog
Separate GLM-Legal's beta access from unconfirmed API terms, interpret its independent benchmark results, and test document evidence with a reviewer-inclusive cost model.
Read Blog
Check the October 17 model update, peak and off-peak token rates, and new search charges, then evaluate an agent against versioned API evidence.
Read Blog
Understand Timestral's time-step limits and weight license, estimate a local forecasting job, and design a retail backtest that cannot see future sales.
Read Blog
Check Sonnet 5.5's token costs, thinking settings and conversation requirements, then evaluate coding changes against a concrete merchant-sorting fixture.
Read Blog
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.
Read Blog