[{"data":1,"prerenderedAt":593},["ShallowReactive",2],{"footer-vacatures-en":3,"use-case-ai-prototype-naar-productie-en":4,"content-by-keys-offers-en-vibe-code-rescue-audit,build-integrate":94,"content-by-keys-useCases-en-ai-experiment-heeft-echte-gebruikers,tests-evals-monitoring-voor-ai":380,"content-by-keys-cases-en-":536,"content-by-keys-buyerTriggers-en-vastgelopen-met-ai":537},[],{"id":5,"title":6,"body":7,"description":11,"desiredOutcome":14,"extension":26,"hero":27,"key":29,"meta":30,"navigation":31,"path":32,"problem":33,"proof":45,"recognition":57,"recommendedApproach":72,"relations":74,"seo":84,"stem":87,"summary":88,"visuals":89,"__hash__":93},"useCases_en\u002Fuse-cases\u002Fai-prototype-naar-productie.md","Our AI prototype has to go to production",{"type":8,"value":9,"toc":10},"minimark",[],{"title":11,"searchDepth":12,"depth":12,"links":13},"",2,[],{"intro":15,"items":16},"You want to keep what the prototype has proven, but reduce the technical risks before the system is used seriously.\n",[17,20,23],{"title":18,"text":19},"Reliable under real conditions","The solution can deal with errors, unexpected input and external systems that don't always cooperate.\n",{"title":21,"text":22},"Measurable behaviour","You can track whether quality, latency, costs and error rates stay within acceptable limits.\n",{"title":24,"text":25},"Manageable in production","Deployment, logging, security and human oversight are part of the system instead of separate aftercare.\n","md",{"intro":28},"A demo may act strangely now and then, production software may not. As soon as an AI prototype touches real users, data and business processes, the requirements change. We help determine what still lies between a successful experiment and a reliable production solution.\n","ai-prototype-naar-productie",{},true,"\u002Fuse-cases\u002Fai-prototype-naar-productie",{"intro":34,"causes":35},"A prototype is built to prove an assumption. Production software has to deal with uncertainty, errors and real users for a long time.\n",[36,39,42],{"title":37,"text":38},"Reliability was not yet a main goal","During an experiment, speed of learning is usually more important than complete error handling.\n",{"title":40,"text":41},"AI does not behave deterministically","Good behaviour has to be measured and bounded instead of only being judged during a demo.\n",{"title":43,"text":44},"The rest of the software now counts","Data, permissions, integrations, deployment and monitoring become just as important as the AI functionality itself.\n",{"intro":46,"points":47},"For us, taking AI to production is mainly software engineering around a non-deterministic component. That calls for regular production-grade principles and AI-specific evaluation.\n",[48,51,54],{"title":49,"text":50},"Beyond the demo","We look at errors, edge cases, integrations and operational behaviour.\n",{"title":52,"text":53},"Human-in-the-loop where needed","Not every risk is solved with more AI.\n",{"title":55,"text":56},"Built for handover","Architecture and choices are recorded so that your own team can continue afterwards.\n",{"intro":58,"signals":59},"The prototype does what it should, but you notice there is still a big gap between demonstrating and going live responsibly.\n",[60,63,66,69],{"title":61,"text":62},"The happy flow works","Demos go well, but edge cases and errors have hardly been worked out.\n",{"title":64,"text":65},"You don't know what good enough is","There are no clear quality thresholds, evals or acceptance criteria yet.\n",{"title":67,"text":68},"Production questions pile up","Security, monitoring, costs, retries, permissions and support suddenly become important.\n",{"title":70,"text":71},"The first real users are coming","You want to prevent them from discovering the technical weak spots for you.\n",{"intro":73},"With a Vibe Code Rescue Audit we first map what stands between the prototype and production. If the route is then large and clear, Build & Integrate can deliver the production version in a controlled way.\n",{"buyerTriggerKeys":75,"primaryOfferKey":77,"offerKeys":78,"caseKeys":80,"relatedUseCaseKeys":81},[76],"vastgelopen-met-ai","vibe-code-rescue-audit",[77,79],"build-integrate",[],[82,83],"ai-experiment-heeft-echte-gebruikers","tests-evals-monitoring-voor-ai",{"title":85,"description":86},"Take an AI prototype to production | 9to5 software","From a working AI prototype to production-ready software. 9to5 helps with architecture, reliability, security, integrations, monitoring and deployment.\n","use-cases\u002Fai-prototype-naar-productie","The prototype proves the idea works. Now it has to become reliable, secure and manageable enough for real users and real business processes.\n",{"hero":90,"problem":91,"proof":92},"sq-foundation-build","sq-guardrails-check","ls-prototype-to-production","jSQ8HzLPrDfgmJ9vRmp8QviUxczEzNXGhTdx2Q7mSaU",[95,239],{"id":96,"title":97,"body":98,"catalogue":102,"cta":103,"description":11,"extension":26,"fit":108,"hero":116,"key":77,"meta":119,"navigation":31,"next":120,"outcome":133,"path":145,"price":146,"process":149,"proof":164,"relations":178,"scope":191,"seo":224,"stem":227,"summary":228,"summaryPanel":229,"visuals":234,"__hash__":238},"offers_en\u002Foffers\u002Fvibe-code-rescue-audit.md","Vibe Code Rescue Audit",{"type":8,"value":99,"toc":100},[],{"title":11,"searchDepth":12,"depth":12,"links":101},[],null,{"title":104,"body":105,"primaryCta":106,"local":107},"No idea what to fix anymore?","Let us first figure out what you actually have. Then you can make a technical decision without blindly prompting on or throwing everything away.\n","Book a Rescue Audit","Vibe Code Rescue by senior engineers from Delft, for teams in Delft, The Hague, Rotterdam and the surrounding area.\n",{"title":109,"intro":110,"useCaseKeys":111},"When is this offer a fit?","When you sense something is technically wrong, but the actual cause or extent isn't clear yet.\n",[112,113,114,115],"vibe-coded-app-professionaliseren","ai-agent-niet-betrouwbaar","gegenereerde-code-niet-meer-begrijpelijk","vibe-code-project-vastgelopen",{"headline":117,"intro":118,"primaryCta":106},"Find out what is really wrong before you rebuild everything.","You already have software, but no longer know which problems are superficial and which are structural. We reconstruct how the system works, separate technical debt from real risks and give you a prioritised route forward.\n",{},{"title":121,"items":122},"What happens next?",[123,127,130],{"title":124,"text":125,"offerKey":126},"A clear rescue goal?","Then we can tackle it in a focused Rescue Sprint.\n","rescue-sprint",{"title":128,"text":129,"offerKey":79},"Turns out to be a bigger build project?","Then we scope Build & Integrate as a fixed engagement.\n",{"title":131,"text":132},"Turns out little is wrong?","Then we'll simply tell you. A follow-up is not required.\n",{"title":134,"items":135},"Afterwards you have...",[136,139,142],{"title":137,"text":138},"Technical grip on what is there","Architecture, key dependencies and critical risks are clear again.\n",{"title":140,"text":141},"A prioritised rescue plan","You know what can stay, what really needs to change and in which order.\n",{"title":143,"text":144},"A decision on the follow-up approach","Fixing, partially rebuilding, developing further at a larger scale or doing nothing becomes a conscious choice.\n","\u002Foffers\u002Fvibe-code-rescue-audit",{"label":147,"type":148},"€2,950 excl. VAT","fixed",{"title":150,"steps":151},"How it works.",[152,155,158,161],{"title":153,"text":154},"Confirm the rescue goal","We determine which questions the Audit needs to answer and where the biggest uncertainty lies.\n",{"title":156,"text":157},"Reconstruct code + system","We read the architecture, code, deployment, data flows and relevant dependencies.\n",{"title":159,"text":160},"Prioritise problems","We distinguish cosmetic debt, development blockers and real production or security risks.\n",{"title":162,"text":163},"Rescue plan + debrief","You get a concrete route with what can stay, what needs to change and what makes sense next.\n",{"title":165,"intro":166,"points":167,"caseKeys":177},"Why should you believe this?","Assessing an existing codebase takes more than an automated quality score. It takes senior engineers who can see which problems actually hurt.\n",[168,171,174],{"title":169,"text":170},"Existing software is where we work","A messy or AI-generated codebase is no reason to automatically start over.\n",{"title":172,"text":173},"Software engineering and AI","We look at both regular production-grade problems and AI-specific failure modes.\n",{"title":175,"text":176},"Follow-up work is not a requirement","If the best conclusion is that your current route is fine, the engagement can end there.\n",[],{"buyerTriggerKeys":179,"useCaseKeys":180,"relatedOfferKeys":189,"caseKeys":190},[76],[112,29,113,114,181,182,183,184,185,186,82,187,188,115],"ai-code-breekt-steeds","security-en-privacy-ai-oplossing","ai-oplossing-te-langzaam","ai-oplossing-te-duur","technische-second-opinion-ai","ai-project-overnemen-van-andere-leverancier","prototype-naar-onderhoudbaar-softwareproduct","weg-bij-ai-platform-of-leverancier",[126,79],[],{"title":192,"intro":193,"activities":194,"deliverables":206,"exclusions":217},"What is included in this offer?","A technical diagnosis of one existing application or codebase, aimed at decision-making.\n",{"intro":195,"items":196},"We look broadly enough to find structural causes, without turning it into a theoretical code review.\n",[197,198,199,200,201,202,203,204,205],"Examining architecture and code quality","Assessing dependencies and technical debt","Reviewing authentication and authorisation","Examining the data layer and relevant integrations","Assessing deployment and error handling","Reviewing tests, logging and monitoring","Listing security risks at a high level","Examining AI-specific failure modes","Assessing maintainability and lock-in",{"intro":207,"items":208},"You get a technical verdict you can actually base a follow-up on.\n",[209,210,211,212,213,214,215,216],"Architecture overview","Prioritised list of problems and risks","What can stay","What needs to be adjusted","What may need to be redone","Advice: fix \u002F partially rebuild \u002F rebuild","Proposed order and size of the follow-up","Technical debrief with a senior engineer",{"intro":218,"items":219},"The Audit delivers understanding and a plan. Major fixes don't quietly become part of the analysis.\n",[220,221,222,223],"Full repair of the codebase","Complete rewrite","Unbounded pentest or formal security audit","Product development beyond small diagnostic changes",{"title":225,"description":226},"Vibe Code Rescue Audit | Stuck with AI code | 9to5 software","Vibe-coded app (Lovable, Cursor, Bolt, Replit) or AI project stuck? 9to5 examines architecture, code, security, tests and deployment and gives you a rescue plan.\n","offers\u002Fvibe-code-rescue-audit","We examine what you have, what can stay as it is, where the real risks are and how you can move forward responsibly again.\n",{"qualifier":230,"result":231,"duration":232,"nextStep":233},"Fixed price · one existing application or codebase","Technical grip on what exists and a prioritised rescue plan","About two weeks","A Rescue Sprint for the most important problem, or continue yourself",{"hero":235,"proof":236,"process":237},"sq-tangle-knot","sq-orient-options","ls-route-converge","IWSlwlvSU82rOHwWTXtSCvLbfXjNUybu2L5bZ-96IJY",{"id":240,"title":241,"body":242,"catalogue":246,"cta":257,"description":11,"extension":26,"fit":262,"hero":269,"key":79,"meta":272,"navigation":31,"next":273,"outcome":285,"path":296,"price":297,"process":300,"proof":314,"relations":327,"scope":338,"seo":367,"stem":370,"summary":371,"summaryPanel":372,"visuals":377,"__hash__":379},"offers_en\u002Foffers\u002Fbuild-integrate.md","Build & Integrate",{"type":8,"value":243,"toc":244},[],{"title":11,"searchDepth":12,"depth":12,"links":245},[],{"audience":247,"promise":248,"deliverables":249,"note":255,"visual":256},"For organisations that know what needs to be built and want 9to5 to build and integrate it professionally.\n","Not an AI demo, but something that works with your real software, data, processes and people.\n",[250,251,252,253,254],"Architecture and production-ready implementation","Integrations with existing software and data","Permissions, error handling and human oversight","Tests, monitoring and deployment where relevant","Documentation and handover to your team","We define the scope together first, then agree a fixed price for the result.\n","ls-system-connect",{"title":258,"body":259,"primaryCta":260,"local":261},"Do you know what needs to be built?","Share the desired outcome and your existing technical context with us. If the scope is clear, we turn it into a fixed engagement.\n","Discuss what you need built","AI engineering and software implementation from Delft, for organisations in Delft, The Hague, Rotterdam and the surrounding area.\n",{"title":109,"intro":263,"useCaseKeys":264},"When the desired outcome is clear enough to scope a professional implementation.\n",[265,266,267,268],"ai-agent-laten-bouwen","interne-ai-assistent-laten-ontwikkelen","bedrijfsproces-automatiseren-met-ai","ai-toevoegen-aan-bestaande-software",{"headline":270,"intro":271,"primaryCta":260},"Not an AI demo, but something that works with your real software, data and people.","The problem and the desired direction are clear. Now it has to be built properly. We take on architecture, AI, integrations and production-grade engineering as one whole and hand it back over afterwards.\n",{},{"title":121,"items":274},[275,278,281],{"title":276,"text":277},"You take it over","That is what we work towards. We don't want you to keep needing us.\n",{"title":279,"text":280},"A new bounded question comes up later","Then we scope it again instead of automatically keeping capacity running.\n",{"title":282,"text":283,"offerKey":284},"Still too much technical uncertainty?","Then an AI Prototype Sprint or Reality Check before Build & Integrate may be wiser.\n","ai-prototype-sprint",{"title":134,"items":286},[287,290,293],{"title":288,"text":289},"Working software instead of a demo","The agreed functionality works end to end within the real technical environment.\n",{"title":291,"text":292},"Reliable integration with what is already there","Data, systems, permissions and human processes are part of the solution.\n",{"title":294,"text":295},"A product you can hand over","Architecture, code and key choices are documented well enough to continue independently.\n","\u002Foffers\u002Fbuild-integrate",{"label":298,"type":299},"Fixed price after scoping","scoped",{"title":150,"steps":301},[302,305,308,311],{"title":303,"text":304},"Scope + success criteria","We make exact enough what needs to work to agree on responsibility and price.\n",{"title":306,"text":307},"Architecture + integrations","We determine how AI, data, existing software, permissions and users come together.\n",{"title":309,"text":310},"Build + test","We implement the hard part and also test errors, edge cases and reliability.\n",{"title":312,"text":313},"Go live + hand over","We bring the solution to production in a controlled way, document it and hand it over.\n",{"title":165,"intro":315,"points":316,"caseKeys":326},"AI only becomes truly valuable when it works together with existing software, data and business processes. That is simply serious software engineering.\n",[317,320,323],{"title":318,"text":319},"The same people advise and build","Advice and execution sit with the same technical people.\n",{"title":321,"text":322},"Integrations are core work","We don't treat APIs, databases, auth and existing systems as an afterthought around the AI.\n",{"title":324,"text":325},"Production and handover are part of it","The work isn't done when the demo works, but when the solution is manageable.\n",[],{"buyerTriggerKeys":328,"useCaseKeys":330,"relatedOfferKeys":335,"caseKeys":337},[329,76],"ai-laten-bouwen",[265,266,267,268,331,332,333,334],"eigen-data-en-kennis-gebruiken-met-ai","documenten-en-mails-automatisch-verwerken","agentic-workflows-bestaande-software","tools-vervangen-door-maatwerkflow",[336,284,77,126],"ai-reality-check",[],{"title":192,"intro":339,"activities":340,"deliverables":351,"exclusions":360},"The scope is defined up front. Then you get a fixed price for the agreed result.\n",{"intro":341,"items":342},"The exact work differs per engagement, but we take responsibility for the complete technical result.\n",[343,344,345,346,347,348,349,350],"Making scope and success criteria concrete","Designing the architecture","Implementing AI functionality or an agent flow","Building integrations with existing software and data","Setting up authentication, authorisation and data flows properly","Tests, evals, monitoring and error handling where relevant","Deployment and production setup","Documentation and technical handover",{"intro":352,"items":353},"The deliverables are defined per scope and are part of the fixed price.\n",[354,355,356,357,358,359],"Working agreed functionality","Production-grade implementation","Required integrations","Relevant tests and quality checks","Technical documentation","Deployment and handover as scoped",{"intro":361,"items":362},"No unbounded consultancy and no feature list that keeps growing afterwards.\n",[363,364,365,366],"Functionality outside the agreed scope","Ongoing retainer as a standard component","External model, API and hosting costs","Additional work without a new explicit scope and price",{"title":368,"description":369},"Have AI built and integrated | Build & Integrate | 9to5 software","Have an AI agent, internal tool, MCP integration or AI feature built with Claude or ChatGPT\u002FOpenAI and professionally integrated with your software, data and processes.\n","offers\u002Fbuild-integrate","You know what needs to be built. We build it professionally, connect it to your existing software and make sure it can be handed over production-ready.\n",{"qualifier":373,"result":374,"duration":375,"nextStep":376},"Fixed price after joint scoping","Working, integrated software your team can take over","Set in the scope","Handover to your team, or further development together",{"hero":378,"proof":90,"process":256},"sq-connect-nodes","jlXsSL_a-hghGaOxvEHbZ2ARDUkoaAlfXaEkKLzQpSQ",[381,458],{"id":382,"title":383,"body":384,"description":11,"desiredOutcome":388,"extension":26,"hero":400,"key":82,"meta":402,"navigation":31,"path":403,"problem":404,"proof":416,"recognition":428,"recommendedApproach":443,"relations":445,"seo":450,"stem":453,"summary":454,"visuals":455,"__hash__":457},"useCases_en\u002Fuse-cases\u002Fai-experiment-heeft-echte-gebruikers.md","Our experiment became unexpectedly successful and suddenly has real users",{"type":8,"value":385,"toc":386},[],{"title":11,"searchDepth":12,"depth":12,"links":387},[],{"intro":389,"items":390},"You don't want to slow down growth, but you also don't want to wait until the first serious outage, security flaw or cost explosion forces you to act.\n",[391,394,397],{"title":392,"text":393},"The biggest risks under control","Security, data, deployment and reliability get the attention that real use requires.\n",{"title":395,"text":396},"Growth stays manageable","More users does not automatically mean proportionally more technical problems.\n",{"title":398,"text":399},"The experiment can become a product","The most important prototype shortcuts are deliberately kept or replaced.\n",{"intro":401},"Good news: people want to use your product. Less good news: the software was never built for that. We help make sure unexpected success doesn't turn into a technical incident.\n",{},"\u002Fuse-cases\u002Fai-experiment-heeft-echte-gebruikers",{"intro":405,"causes":406},"Prototype choices were made for speed of learning. Success suddenly changes the requirements the same software has to meet.\n",[407,410,413],{"title":408,"text":409},"Operational requirements came later","Monitoring, backups, support and scalability were, logically enough, no priority during the experiment.\n",{"title":411,"text":412},"The user population changes","Real users do things the original test team never thought of.\n",{"title":414,"text":415},"Business value raises technical risk","As soon as people depend on the system, downtime has a different impact.\n",{"intro":417,"points":418},"We don't make everything enterprise-grade by default. The point is to work out which engineering you need now to keep growing responsibly.\n",[419,422,425],{"title":420,"text":421},"Risk-driven professionalisation","We first tackle what really threatens users, data or continuity.\n",{"title":423,"text":424},"Keep prototype knowledge","Working parts are not replaced just because they started as an experiment.\n",{"title":426,"text":427},"Ready for the next phase","The technical foundation grows along with actual product use.\n",{"intro":429,"signals":430},"The technology is often fine, but built for a very different scale and expectation.\n",[431,434,437,440],{"title":432,"text":433},"Support questions suddenly come in","Users expect availability and predictable behaviour.\n",{"title":435,"text":436},"Accounts and permissions become important","What was first one internal experiment now has different users and roles.\n",{"title":438,"text":439},"Costs start to stand out","Model and infrastructure usage suddenly grows along with real use.\n",{"title":441,"text":442},"You're afraid to make big changes","The software is now important enough that downtime or data loss hurts.\n",{"intro":444},"A Vibe Code Rescue Audit first helps determine what is truly urgent now. We can then choose between focused Rescue Sprints and a larger Build & Integrate engagement to professionalise the product further.\n",{"buyerTriggerKeys":446,"primaryOfferKey":77,"offerKeys":447,"caseKeys":448,"relatedUseCaseKeys":449},[76],[77,79],[],[29,187],{"title":451,"description":452},"AI experiment suddenly has real users | 9to5 software","AI experiment unexpectedly successful? 9to5 helps you scale your prototype safely, reliably and maintainably to real use.\n","use-cases\u002Fai-experiment-heeft-echte-gebruikers","What started as an experiment is actually being used. Now the technology has to mature faster than originally planned.\n",{"hero":90,"problem":456,"proof":92},"sq-bottleneck-pressure","xBug-F1_Gp1DHk40W3mSx2FhRCmjWWw1lcKDGuJ_ghA",{"id":459,"title":460,"body":461,"description":11,"desiredOutcome":465,"extension":26,"hero":477,"key":83,"meta":479,"navigation":31,"path":480,"problem":481,"proof":493,"recognition":505,"recommendedApproach":520,"relations":522,"seo":527,"stem":530,"summary":531,"visuals":532,"__hash__":535},"useCases_en\u002Fuse-cases\u002Ftests-evals-monitoring-voor-ai.md","We're missing tests, evals or monitoring",{"type":8,"value":462,"toc":463},[],{"title":11,"searchDepth":12,"depth":12,"links":464},[],{"intro":466,"items":467},"You want to change things with confidence because you quickly see what a new prompt, model version or code change actually does.\n",[468,471,474],{"title":469,"text":470},"Regressions become visible","Important existing situations are automatically checked again.\n",{"title":472,"text":473},"AI quality becomes measurable","You compare changes against relevant examples and criteria.\n",{"title":475,"text":476},"Production gives feedback","Errors, latency and unusual behaviour no longer disappear quietly into logs.\n",{"intro":478},"\"It feels better\" is not a reliable test strategy. If you use AI functionality seriously, you need to be able to see what changes do and when things go wrong in production. We help set up that feedback loop.\n",{},"\u002Fuse-cases\u002Ftests-evals-monitoring-voor-ai",{"intro":482,"causes":483},"Traditional software tests remain important, but AI adds behaviour for which there isn't always one exactly correct answer.\n",[484,487,490],{"title":485,"text":486},"AI output is probabilistic","Exact string comparisons are not enough for many AI tasks.\n",{"title":488,"text":489},"Good examples aren't recorded","Knowledge of what is right and wrong mainly lives in heads and scattered chats.\n",{"title":491,"text":492},"Observability stops at technical errors","An HTTP 200 says nothing about the quality of the answer.\n",{"intro":494,"points":495},"A measurement layer is only useful to us if it helps engineers see faster whether a change is safe and actually better.\n",[496,499,502],{"title":497,"text":498},"Regular tests where possible","Deterministic software simply stays deterministically testable.\n",{"title":500,"text":501},"Evals where needed","AI behaviour gets examples and criteria that fit the real use case.\n",{"title":503,"text":504},"Production data closes the loop","Monitoring shows which real-world situations need attention.\n",{"intro":506,"signals":507},"Without a good feedback loop, an AI product becomes harder and harder to develop responsibly.\n",[508,511,514,517],{"title":509,"text":510},"Testing is mostly manual","After every change someone tries a few known examples.\n",{"title":512,"text":513},"Prompt changes are hard to compare","You can't objectively tell whether version B is really better than version A.\n",{"title":515,"text":516},"Production errors are discovered by users","The system itself hardly flags deviating behaviour.\n",{"title":518,"text":519},"Model updates feel risky","A new provider or model version can change behaviour without clear warning.\n",{"intro":521},"If the scope is clear, we set up a practical feedback loop in a Rescue Sprint with the right combination of tests, evals, traces and monitoring. If broader research is needed first, we start with an audit.\n",{"buyerTriggerKeys":523,"primaryOfferKey":126,"offerKeys":524,"caseKeys":525,"relatedUseCaseKeys":526},[76],[126,77],[],[113,181],{"title":528,"description":529},"Tests, evals and monitoring for AI | 9to5 software","AI without proper tests, LLM evals or monitoring? 9to5 helps set up measurable quality, regression tests and production observability.\n","use-cases\u002Ftests-evals-monitoring-voor-ai","The AI functionality runs, but nobody can objectively see whether changes make it better, worse or quietly break something.\n",{"hero":91,"problem":533,"proof":534},"sq-process-steps","ls-workflow-flow","HLgbDqrGnq-G64ciWMNMDChkwkuEQEyI9a7eCclpOe0",[],[538],{"id":539,"title":540,"approach":541,"body":555,"cta":559,"description":11,"extension":26,"hero":562,"key":76,"label":564,"meta":565,"navigation":31,"path":566,"proof":567,"relations":578,"seo":585,"stem":588,"summary":589,"visuals":590,"__hash__":592},"buyerTriggers_en\u002Fbuyer-triggers\u002Fvastgelopen-met-ai.md","We've already built something, but we're stuck.",{"title":542,"steps":543},"We step in, understand, repair and hand over.",[544,546,549,552],{"title":153,"text":545},"We establish what is actually going wrong, what is urgent and what needs to be demonstrably better after the rescue.\n",{"title":547,"text":548},"Understand the context and code","We examine the code, architecture, data flows, integrations and deployment until the source of the problem is clear.\n",{"title":550,"text":551},"Fix and test","We make targeted repairs, add tests, evals and guardrails where needed and check that the solution works under real conditions too.\n",{"title":553,"text":554},"Document and hand over","We document decisions, clear critical technical debt and make sure your team can move forward independently again.\n",{"type":8,"value":556,"toc":557},[],{"title":11,"searchDepth":12,"depth":12,"links":558},[],{"title":560,"body":561},"Stuck with AI or vibe-coded software?","Briefly describe what you have and where it is going wrong. We'll take a look and quickly tell you what makes sense to repair, keep or rebuild.\n",{"intro":563},"You don't have to start over just because things have become complicated. We step in, including when you have a vibe-coded app or code generated by AI tools such as Claude Code, Codex or Cursor. We understand what is there, find what is really going wrong and make it technically manageable again.\n","Stuck with AI",{},"\u002Fbuyer-triggers\u002Fvastgelopen-met-ai",{"intro":568,"points":569},"Assessing an existing codebase takes more than an automated quality score. It takes senior engineers who can identify the problems that really hurt and make targeted repairs.\n",[570,573,575],{"title":571,"text":572},"We work with existing software","A messy or AI-generated codebase is no reason to automatically start from scratch.\n",{"title":172,"text":574},"We look at everyday production problems and AI-specific failure modes, such as unreliable output and missing evals.\n",{"title":576,"text":577},"Move forward independently again","We document decisions and clear critical technical debt so your team can move forward on its own again.\n",{"useCaseKeys":579,"offerKeys":583,"caseKeys":584},[112,29,113,114,181,580,581,182,183,184,83,582,185,186,82,187,188,115],"vast-op-auth-database-of-rechten","ai-koppelen-aan-bestaande-systemen","developmentteam-loopt-vast-met-ai",[77,126,79],[],{"title":586,"description":587},"Stuck with AI? Rescue by senior engineers | 9to5 software","Stuck with an AI agent, prototype or vibe-coded app (Lovable, Cursor, Bolt, Replit)? We analyse the problem, make targeted repairs and restore maintainability.\n","buyer-triggers\u002Fvastgelopen-met-ai","Something is already there, but it is unreliable, hard to understand or technically stuck. We need to get it back under control.\n",{"hero":235,"proof":591,"approach":591},"ls-rescue-repair","e0bDu3r1P4JqQOadOsQgPsL_EDOsQGpgsqBXrdwFTNw",1792049911721]