Proceed
The central assumptions have enough support to scope implementation.
Explore MVP BuildResearch, prototypes and technical exploration before you commit to development.
Reveal a fictional observation to see how it changes the next prototype.
Evidence not yet reviewedThe central assumptions have enough support to scope implementation.
Explore MVP BuildAdjust the audience, journey or technical approach and test again.
Keep the evidence and avoid a build commitment that it does not support.

An opening film, image-led scrolling and a dedicated mobile experience.
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A shared-hosting application with encrypted document storage and a staff review console.
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Supplier-data scraping and AI engineering for a cross-border shopping and warehouse platform.
View projectA customer problem, access to relevant stakeholders and any existing research or product material. A detailed specification is not required.
Participant access and recruitment responsibilities are agreed in scope. We identify which user groups need to be represented before planning sessions.
No. A discovery prototype is used to test interactions and assumptions. Production implementation, hosting and operational work are scoped separately.
The decision may be to narrow the scope, change the journey, investigate further or stop. Discovery should make that choice more informed, rather than guarantee a build recommendation.
Yes. The agreed handover can include the evidence, prototype, backlog and technical decisions needed by your internal team or another delivery partner.
The number of user groups, uncertainty in the workflow, access to evidence and technical questions determine the scope. Dates and milestones are agreed after reviewing those inputs.
Bring the idea, your intended users and the assumption you are least certain about.
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.
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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.
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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.
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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.
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Check the released model's token rates and API compatibility, calculate a realistic pilot budget, and evaluate image evidence against changing inventory records.
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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.
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Check the October 17 model update, peak and off-peak token rates, and new search charges, then evaluate an agent against versioned API evidence.
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Understand Timestral's time-step limits and weight license, estimate a local forecasting job, and design a retail backtest that cannot see future sales.
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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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