Use Cases & Solutions

A capability describes what Context Studios can do technically — for example retrieval-augmented generation or multi-agent orchestration. A use case describes what that technique is used for concretely — a booking system for a dental practice, a quote generator for a plumber, or a multilingual product-description pipeline for a Shopify shop. This hub page collects common use cases we can implement, each with a described architecture, expected investment, and metrics by which success can be measured. For product managers and use-case owners this means you do not enter a discovery call with an open question — you can use our landing pages as a starting point and negotiate deviations from there. We intentionally avoid generic marketing vocabulary; every use case lists the concrete technologies involved. One example: our page on automated offer generation explicitly names the components — current language models for text generation, Puppeteer for PDF export, Convex as data layer, Stripe for payment processing. The MVP fixed fee covers most single-function-assistant use cases; more complex scenarios involving multi-agent coordination are priced separately after scoping.

Which use cases we do not take on

Honest note: not every use case belongs with us. We regularly turn down engagements that either draw no technical benefit from AI or that repackage a classic software project in AI language. Pure CRUD applications without language input, document handling, or autonomous behaviour belong with a traditional software house — we then recommend partner studios from our network. We are equally critical of deepfake applications, automated candidate filters without a human in the loop, and any form of dark pattern. Our target universe are use cases in which an LLM or agent delivers a measurable productivity gain: summarising long documents, multilingual content production, semantic search in proprietary knowledge bases, voice interfaces for field service staff, automated quote generation. Each of those categories is documented on a dedicated landing page, including an honest discussion of limitations. If your use case is not listed but you feel it lives in a grey area, drop us a line — we get back to you with a plain go-or-no-go assessment.

From use case to production architecture

Every use-case page follows a fixed structure so that you can orient quickly. After the hero with entity definition follows a chapter on the typical architecture — including a sketch of which components run locally, which in the cloud, and which as SaaS. We then describe the integration path: which systems the use case typically connects to, for example ERP (DATEV, Sage, Odoo), CRM (HubSpot, Pipedrive, Salesforce), or e-commerce platforms (Shopify, Shopware, WooCommerce). The page closes with a price range and timeline — usually four weeks for the MVP followed by two to three iterations of two weeks each. Particularly relevant for product managers: we ship a list of metrics per use case that you can use to measure success (for example first-response time, throughput, quality scores). We agree on those metrics upfront and export them to Grafana or to your existing monitoring. If you are looking for an entry point, sort the list by industry or by technical depth — and book a thirty-minute slot to harden the right use case.