Updated
The first question in most AI conversations is which model to use. That is rarely what decides the outcome. What decides it is which workflow you are automating and what data the model is allowed to see. Curiosive is a software studio run from Ankara, Türkiye, shipping production software for more than five years, with a published portfolio of production work. In several of them AI is not a feature bolted on the side, it is the product.
Define a bounded workflow in the product you already run: the input, permitted data, expected output and who decides whether it is useful. Agree acceptance examples, failure behaviour and operating responsibilities before choosing an implementation. Model choice follows that task rather than setting the scope by itself.
Appster’s published case combines natural-language discovery across more than 2,700 apps, an OpenAI-embedded catalogue, semantic vector search and administration. For another search product, evaluate retrieval examples and how content changes reach the search index. The case establishes delivered search scope, not a universal reduction in response time or cost.
Release Coach AI’s published case describes guided audio prompts and speech recognition in an explicit sequence of session steps, with membership and administration around it. It does not document a LiveKit audio layer or a measured latency result. For a voice integration, define the steps, interruptions, input recognition and fallback behaviour before choosing the audio architecture.
YouNet’s case documents a React and Material UI interface with an embeddable widget, streamed Markdown responses, configurable settings and controls to stop a response or change language. That is interface delivery evidence, not documentation of the platform’s authorization or audit infrastructure. For an agent-enabled workflow, separately define allowed actions, approval points and how decisions will be reviewed.
Test the integration against agreed input and output examples, including provider failure and slow responses. Decide how usage is measured, where limits apply and what the user sees when the workflow cannot finish. Engineers review the application’s data and permission boundaries. These checks help evaluate a release; they do not guarantee a provider’s availability or a predictable bill without actual usage evidence.
This service scopes an AI feature inside a product. Agentic software engineering describes how coding agents assist implementation under engineer review. A project can use that development method without exposing an AI feature to its users. For a first product assumption, define an MVP scope before expanding the integration.
Start with the task you need to improve. These pages connect a published delivery example to discovery questions for a new engagement.
For US nonprofit networks and funding-information publishers maintaining sourced grant opportunities, reviewed status changes and search results aligned with the published catalog.
Explore the scope and discovery questions →For Kearney showroom and product teams guiding visitors through approved voice-demo steps tied to explicit product models and language editions.
Explore the scope and discovery questions →For Walla Walla winery teams connecting embedded visitor help to approved individual and group-visit information with deliberate booking and staff-contact destinations.
Explore the scope and discovery questions →For Framingham workshop teams connecting live session questions, host review and follow-up context across a real-time participant interface.
Explore the scope and discovery questions →For Conway directory publishers connecting natural-language service requests to maintained company records and distinct branch-specific information.
Explore the scope and discovery questions →For Roswell event teams collecting exhibitor documents with event-edition identity, source-linked draft extraction and staff review.
Explore the scope and discovery questions →For Huntsville commercial property teams connecting tenant requests, property and suite references, staff triage and contractor task assignments.
Explore the scope and discovery questions →For Newport museum-product teams connecting exhibit stops, approved audio chapters and bounded voice-navigation controls with manual alternatives.
Explore the scope and discovery questions →For Hattiesburg equipment-software teams connecting source-manual editions, translated sections and explicit reviewer approval before publication.
Explore the scope and discovery questions →For Stamford event-platform teams connecting an event brief, maintained vendor specialties and a reviewed enquiry shortlist without implying confirmed availability.
Explore the scope and discovery questions →For Lubbock theater teams connecting production membership, session-specific cast and crew calls, rehearsal tasks and explicit attendance responses.
Explore the scope and discovery questions →For Wenatchee orchard teams connecting an embedded customer-help interface to current-season visitor information and deliberate staff follow-up.
Explore the scope and discovery questions →For Decatur choir-product teams connecting director-approved rehearsal parts, guided session steps and self-marked practice progress.
Explore the scope and discovery questions →For Cedar Rapids coworking-directory teams connecting plain-language workspace preferences to maintained space records and explicit amenity filters.
Explore the scope and discovery questions →For Akron industrial-software teams connecting supplier document versions, extracted fields and source references to a reviewed internal record.
Explore the scope and discovery questions →For Bend equipment-rental teams connecting website help to the selected item, approved rental information and a clearly scoped staff question.
Explore the scope and discovery questions →For Flagstaff sports-club teams connecting individual practices and club events to their own participant responses, tasks and clearly scoped series changes.
Explore the scope and discovery questions →For Monterey language-learning product teams connecting an approved spoken scenario, dialogue turns and lesson revisions to an understandable practice attempt.
Explore the scope and discovery questions →For Sedona hospitality teams developing a website concierge widget around approved guest information, clear visitor controls and a deliberate staff-contact path.
Explore the scope and discovery questions →For Durham recruitment-platform teams helping visitors discover published opportunities through natural-language search and explicit catalogue filters.
Explore the scope and discovery questions →For Iowa City research-software teams connecting document processing to source-aware review, explicit job states and deliberate output export.
Explore the scope and discovery questions →For Savannah nonprofits developing volunteer event workspaces that connect responsibilities, participant access and coordinator-reviewed changes.
Explore the scope and discovery questions →For Las Vegas event-software teams keeping shared cost records, participant context and corrections within the intended event workspace.
Explore the scope and discovery questions →For Rochester, New York coaching-product teams making prompt playback, listening and retry states clear within an approved guided voice sequence.
Explore the scope and discovery questions →For Memphis community-product teams returning a disconnected participant to the intended topic room with understandable pending-message behavior.
Explore the scope and discovery questions →For Spokane software-directory teams helping visitors refine a natural-language request and understand the catalogue results it returns.
Explore the scope and discovery questions →For Cleveland healthcare product teams connecting a translated document and structured report to the source a professional needs to review.
Explore the scope and discovery questions →For Anchorage event-software teams keeping a participant's mobile task update connected to the organizer's shared event plan.
Explore the scope and discovery questions →For Fargo AI product teams making streamed responses, visitor stop controls and conversation-language changes understandable in an embedded chat.
Explore the scope and discovery questions →For Jackson healthcare product teams giving operators a clear recovery path when document extraction or report processing stops.
Explore the scope and discovery questions →For Pittsburgh community-product teams connecting topic discovery and a shared live conversation across web and mobile.
Explore the scope and discovery questions →For Indianapolis voice-coaching product teams connecting guided sessions to an understandable member dashboard and progress history.
Explore the scope and discovery questions →For Providence event-software teams modernizing an active planning interface while keeping an established backend.
Explore the scope and discovery questions →For Columbus AI-directory publishers giving editors a clear path from approved app records to public pages and the search index.
Explore the scope and discovery questions →For San Jose AI product teams making agent configuration, embedded previews and conversation controls understandable to business users.
Explore the scope and discovery questions →For Sacramento healthcare product teams connecting mixed-format document intake, processing status and professional review in one application.
Explore the scope and discovery questions →For Portland coaching businesses turning an approved spoken method into guided voice sessions with membership and content operations.
Explore the scope and discovery questions →For Phoenix event-software teams connecting organizers, participants, shared tasks and costs in a collaborative workspace.
Explore the scope and discovery questions →For Los Angeles media and community teams connecting topic discovery to shareable live chat rooms across web and mobile clients.
Explore the scope and discovery questions →For Washington software-directory teams connecting natural-language discovery, structured catalogue records and useful public detail pages.
Explore the scope and discovery questions →For Texas customer-support product teams adding an embeddable AI conversation interface to existing business websites.
Explore the scope and discovery questions →Service scopes for teams serving Sweden, Norway, Denmark and Finland, grounded in published work and proposed first-release checks.
For Nordic software-directory and comparison publishers adding useful natural-language discovery to a maintained catalogue of approved product records.
Explore the scope and discovery questions →For Nordic AI support-product teams bringing an existing agent experience onto customer websites, with reviewable installation settings, host-page interaction and conversation recovery.
Explore the scope and discovery questions →Natural-language discovery across a catalogue of more than 2,700 apps, with semantic vector search, administration and programmatic SEO pages.
Read the case study →A real-time chat product that opens a room for each trending topic, built with React, React Native, Supabase and WebSockets, with Grok AI integration.
Read the case study →A React and Material UI interface for an AI agent platform, including a plug and play chat widget that businesses embed on their own websites.
Read the case study →A React and Supabase platform delivering guided voice sessions for emotional reset, with a members area, trainer program, subscriptions and an admin panel behind it.
Read the case study →A React and Supabase streaming platform with adaptive video, live screening rooms and recommended guided experiences that continue the work after each film ends.
Read the case study →A Next.js and TypeScript rebuild of a Dutch event planning app, with shared tasks, items, costs, chat and AI-assisted event setup on an existing Supabase backend.
Read the case study →A Next.js application and document pipeline that turn patient records in any format or language into structured clinical summaries, using Gemini for extraction.
Read the case study →Senior engineers building your product with AI coding agents: web, mobile, SaaS or browser extension, reviewed before anything ships.
AI-accelerated development, billed monthly. We confirm scope, capacity and start date in writing before checkout.
Usually yes. We start by identifying which workflow actually benefits, then define what data the model can reach and under what permissions. The integration lives inside your existing codebase, so this is not a reason to rewrite a product that is already working.
Choose the provider against the task, data constraints, output quality and operating cost. Appster’s published scope uses OpenAI embeddings and TrendinChat includes Grok AI. Assess how a provider change would affect the actual integration rather than promising that every change can avoid a rewrite.
Define expected usage, measurement and limits for the agreed workflow. Evaluate caching or precomputed search data where they fit, and review what happens at a limit or provider failure. Test with representative traffic; these controls do not establish a fixed bill for unknown future use.
That depends on the provider you choose and the agreement you sign with them. During setup we make the data retention and training settings explicit. We also decide together which fields never reach the model at all, since sensitive values can be stripped from the request.
Coding agents are rewarded for passing tests, not for good design. Here is why codebases degrade over time and how planning first keeps review manageable.
Teams often fix a confused AI coding agent by adding more context. The better fix is structured context: skills, live data access, retrieval and memory.
Reviewing changes made by AI coding agents takes more than a passing test suite. Practical questions for planning, structure and refactoring.
One paragraph on what you are building, roughly when you need it, and who it is for. No brief, no form with fifteen fields.
From the engineer who would do the work, not a sales team. If we are not the right fit we say so, and where possible we point you somewhere better.
Scope, price and timeline in writing before anything is committed. You decide with the numbers in front of you.
No long contract to begin, no lock-in to our tooling, and the code is yours from the first commit.
Start a conversationA short note about the product, the timeline and who it is for is enough to start. You will hear back from the engineer who would do the work, not a sales team.
Ankara / Türkiye · Working across European and US time zones
