US clients ask us

Yes. We build native iOS apps in Swift and native Android apps in Kotlin, as well as cross-platform apps with React Native and Flutter. The right approach depends on your product's requirements. If you need deep platform integration — camera APIs, health data, wearable sync, or payment hardware — native is the right choice. If you need speed to market and one codebase for both platforms, React Native or Flutter gets you there without compromising on feel. We've shipped apps across both approaches and can advise on the tradeoff for your specific case. Every app we build is tested on real devices, not simulators.See our work →

Yes. With React Native or Flutter, we write one codebase that deploys to both iOS and Android — reducing development time and keeping features in sync across platforms. Both frameworks render native UI components, so the app feels like it belongs on each platform rather than a ported version. For apps with intensive graphics, real-time audio, or deep hardware access, we recommend building separate native versions in Swift and Kotlin. The right choice comes down to what your app actually does. We'll give you an honest recommendation after understanding your requirements — not the one that's fastest to build.

Yes. We handle the full release process from first build to live in store. That includes Apple Developer account setup, certificates and provisioning profiles, TestFlight beta distribution, App Store Connect listings, screenshots for every device size, and compliance review for App Store guidelines. On Android: Play Console setup, signed APKs or App Bundles, store listings, and Google's content policy review. We've shipped apps on both platforms and know where submissions get rejected — and how to avoid it. If your app is already live and needs an update, we can take over the release pipeline.

Yes. We build watchOS apps, Apple Watch complications, and wearable extensions for iOS apps. We've shipped watchOS apps with workout tracking, real-time data sync with the paired iPhone, custom watch faces, and background sensor polling. Wearables are a meaningful second surface for health apps, fitness products, and anything where a glanceable notification or quick action matters. We evaluate whether watchOS adds real value for your users before building it — a watch extension that's just a shrunk phone screen isn't useful. When it is the right tool, we build it with full Siri integration, health data access, and offline capability.See Audra →

Yes. We use the official WhatsApp Business API and Telegram Bot API — not unofficial workarounds that can get your account banned. We build bots that handle customer service at scale, capture and qualify leads, manage bookings, send transactional messages, and run structured conversation flows for onboarding or sales. Every bot connects to your existing systems: your CRM, your calendar, your database, your payment processor. We've built bots that handle thousands of conversations per day without a human in the loop — and bots that escalate intelligently to a human agent when the conversation needs it.

Yes. We build end-to-end conversational flows that complete transactions — not just collect names and email addresses. For payments, we integrate Stripe, Mercado Pago, or your existing processor so a customer can pay within the conversation. For bookings, we connect to Calendly, Google Calendar, or your own booking system so a slot is confirmed in real time. For support, we build tiered logic: the bot handles common questions from a knowledge base, escalates edge cases to a human, and logs everything to your CRM. The goal is a bot that closes the loop — not one that dead-ends into 'please call us'.

We work across all the major models: GPT-4o, Claude 3.5 and 3.7, Gemini 1.5 and 2.0 Flash, Llama 3, Mistral, and open-source alternatives. Model selection depends on your use case, latency requirements, and budget. For structured reasoning and tool-use tasks, Claude and GPT-4o perform consistently. For high-volume tasks at lower cost, Gemini Flash and Mistral are worth evaluating. For fully private deployments where data cannot leave your infrastructure, we run open-source models on your own cloud. We benchmark models against your specific tasks before committing to a choice — not based on what's trending online.

Yes — with proper design. We build agents with explicit decision boundaries: a defined set of tasks the agent handles autonomously, and a clear escalation path when the task falls outside those boundaries. Every agent action is logged to an audit trail so you can see exactly what decisions were made and why. We test edge cases before deployment, not after. For fully automated workflows — data processing, content generation, lead qualification, monitoring — the agent runs without supervision. For workflows that touch money, legal decisions, or sensitive customer interactions, we design intelligent handoff to a human at the right moment. Autonomous doesn't mean unaccountable.

A chatbot follows a fixed script — it matches your input to a predetermined response and cannot take actions in the world. An AI agent perceives its environment, makes decisions, and executes actions autonomously: it can call APIs, read databases, send emails, update CRM records, trigger payments, and loop through multi-step tasks without a human directing each step. The key distinction is agency: a chatbot answers questions, an AI agent gets things done. Most business automation problems that feel complex are actually straightforward for a well-designed agent — the hard work is defining the decision boundaries and building the right integrations. We build both, and we'll tell you honestly which one solves your actual problem.

Business process automation (BPA) is the use of software to execute repeating, rule-based tasks that would otherwise require manual effort — data entry, document routing, approval workflows, reporting, notification triggers, and system synchronization across tools. At KAUFAST, automation typically involves connecting your existing platforms (your CRM, your ERP, your e-commerce stack, your calendar, your accounting software) through APIs and event-driven logic, so information flows without anyone copying it between tabs. The result is fewer errors, faster cycle times, and staff freed from administrative overhead. A well-scoped automation engagement typically ships in 2–4 weeks and pays for itself within the first quarter.

Yes. We build internal operations tools, client-facing analytics portals, admin panels, and real-time data dashboards. The starting point is always the same: what decisions does this dashboard help you make? A good dashboard surfaces the number that tells you whether to act — not a wall of charts. We've built dashboards that aggregate data from multiple APIs, dashboards with real-time WebSocket updates, and client portals that give customers a plain-language view of their performance. If your team exports data to a spreadsheet every Monday morning to understand last week, we can replace that workflow with something that works in real time.See KAUFAST dashboard →

Primarily Next.js and React on the frontend — this site is built on Next.js and achieves 100/100 on Google's performance audit, which is the benchmark we hold our work to. On the backend, Node.js and TypeScript for most projects; Go or Python where performance or data processing demands it. For APIs: REST for simplicity, GraphQL where flexible querying matters, tRPC for full-stack TypeScript teams. For databases: Postgres for most applications, MongoDB for document-heavy workloads, Redis for caching and real-time features. We recommend the stack that fits your team's skills and your product's demands — not the one we used last time.

Yes. We've built multi-tenant SaaS products where each customer has their own data partition, role-based permissions, and custom configuration. We've built two-sided marketplaces with separate buyer and seller flows, escrow logic, and fee structures. We've built subscription platforms with Stripe billing, trial periods, upgrade paths, and usage-based pricing. The pieces that SaaS products always need — authentication, team management, billing, audit logs, email notifications, and admin tooling — we've built them so many times we have patterns for them. For an early-stage product, we'll advise which you need from day one and which can wait until you have paying users.

Performance starts at the data layer. We design the database schema and query patterns before writing frontend code — an expensive query that runs on every page load will kill a dashboard no matter how the frontend is built. For real-time data, we use WebSockets or server-sent events so the UI updates as data changes, without polling every few seconds. For historical data, we use smart caching: pre-computed aggregations, incremental static regeneration for data that changes slowly, and time-windowed queries that don't scan the full dataset. The goal is a dashboard that feels instant because the hard work happens before the user even clicks.

Yes. Technical SEO means making your site structurally sound so search engines can find, read, and understand every page — clean URL architecture, fast load times, proper schema markup, hreflang for international sites, and passing Core Web Vitals scores. Content strategy means publishing content that answers the specific questions your customers are searching for — and that AI models cite when generating answers. We don't buy links or pad pages with keywords. We've built this site across 13 locales and maintained 95+ mobile performance scores while doing it. Every SEO recommendation we make, we apply to our own site first.See SEO services →

Honestly: 3–6 months for meaningful ranking movement, 6–12 months for compound gains that build on each other. That's not a disclaimer — it's the reality of how Google's indexing and trust-building works. We don't make promises we can't keep. What we do commit to is showing you exactly what we're doing and why at every stage: which pages we're improving, what keywords are moving, and what the traffic impact is. Technical fixes often show results faster — sometimes within weeks. New content takes longer. The work that takes the longest also tends to have the highest lifetime value.

Yes. International SEO is significantly more complex than single-language SEO — and it's one of our specialties. We implement hreflang tags correctly (most implementations are misconfigured and ignored by Google), locale-specific sitemaps, geo-targeted server-side rendering, and content strategies tailored to each market rather than direct translation. Keyword research differs by country: the words a Spanish speaker in Spain uses are not the same as a Spanish speaker in Mexico. We handle both the technical layer and the content layer. This site runs in 13 locales, achieves Page 1 rankings across multiple markets, and is maintained as part of our own SEO program.

Yes, and it's some of the work we enjoy most. With early-stage founders, we do what matters most first: get something real in front of real users as quickly as possible. That means making deliberate architectural choices upfront so the codebase doesn't need to be rebuilt at Series A, and saying no to features that don't matter yet. We've helped bootstrapped products reach enterprise clients, VC-backed teams ship faster than their runway allowed, and first-time founders build products they were told would take years. The best time to get the architecture right is before you have a million users depending on it.

We believe in full transparency — our starting prices are published on our pricing page with no "contact us for a quote" runaround. A focused automation or AI agent engagement starts from €4,000. A monthly retainer for ongoing development starts from €2,000. A strategic consulting engagement starts from €1,500. These are starting points, not ceilings — complex platforms cost more, and we'll scope that honestly before you commit. What we don't do: hidden fees, scope creep billed without approval, or vague estimates that change once the contract is signed. You know exactly what you're paying for before we start.See our pricing →

A focused automation, AI agent, or WhatsApp bot ships in 2–4 weeks — that's a fully functional, deployed product, not a prototype. A full mobile app or web platform: 3–6 months with usable features delivered every two weeks, so you're testing with real users before the project ends. An enterprise platform migration or multi-system integration: 6–12 months with measurable milestones throughout. In every case, we define scope and milestones before we start — in writing. Changes to scope happen through a formal process with agreed cost and timeline impact. No surprises at invoice time.

Yes. After launch, we offer 24/7 system monitoring so problems are caught before your users notice them. Incident response when something breaks — we aim to be looking at the issue within 30 minutes of an alert. Performance tuning as your traffic grows and usage patterns change. Feature development as your product evolves and new requirements emerge. Some clients run on a monthly retainer for continuous development and priority support. Others engage us for specific feature work when they need it. We don't disappear after the handoff — the codebase we built is our reputation, and we want it to keep working.

Book a free discovery call — no commitment, no sales pitch, no follow-up sequence if we're not a fit. On the call, we'll ask about what you're building, where you are now, and what success looks like. We'll tell you honestly whether we think we're the right team for it — and if we're not, we'll say so rather than take the project anyway. If we are a fit, we'll outline a clear path forward: scope, timeline, and investment. Most discovery calls run 30–45 minutes. You'll come away with a concrete picture of what building with us looks like — even if you don't move forward.Book a discovery call →

Primarily AWS, Google Cloud Platform, and Vercel — the choice depends on your workload and existing infrastructure. AWS suits data-heavy applications, complex microservice architectures, and regulated industries requiring specific compliance certifications (SOC 2, HIPAA, ISO 27001). Google Cloud is the right choice when your data strategy is built around BigQuery, Vertex AI, or Firebase. Vercel is the fastest path to globally distributed Next.js deployments with ISR, edge functions, and serverless databases. We're platform-agnostic — we recommend based on your requirements, your team's familiarity, and the long-term cost profile. We don't have a preferred-vendor relationship that biases the recommendation.

A straightforward application lift-and-shift — moving a working system from one hosting provider to another without changing the architecture — typically takes 4–8 weeks including testing and cutover. A re-architecture migration, where legacy infrastructure is redesigned for cloud-native services (auto-scaling, managed databases, containerization), takes 3–6 months depending on system complexity. Full enterprise migrations with multiple interconnected systems, data pipeline redesign, and compliance validation take 6–12 months. All migrations are structured in phases with zero-downtime cutover strategies, so your service stays live throughout the transition. We define rollback plans before we start, not after something goes wrong.

Yes — and this is worth understanding before you build. AI models are updated by their providers (OpenAI, Anthropic, Google), which can change behavior even without you touching your code. Prompts that worked perfectly with one model version may produce different outputs with the next. Beyond model drift, agents that interact with external APIs need updates when those APIs change their schemas or rate limits. We recommend a light monthly maintenance retainer for any production agent: model performance monitoring, regression testing, and prompt tuning. For high-volume agents processing thousands of transactions per day, we set up automated evaluation pipelines that flag quality degradation before it reaches users.

Yes. Enterprise CRM and ERP integration is a core part of our automation practice. We connect AI agents to Salesforce via the REST and Bulk APIs, HubSpot via its CRM API and webhooks, and SAP via BAPIs, RFC, or OData services depending on your version and configuration. The pattern is the same in each case: the agent is given tools — structured API calls it can invoke — and decides autonomously which tool to use and when. We've integrated agents with Pipedrive, Zoho, Microsoft Dynamics, Oracle NetSuite, and custom internal systems. If it has an API or can emit webhooks, we can build an agent that works with it.