{ "slug": "platform", "url": "https://www.cheeky-fit.com/platform", "path": "/platform", "json": "https://www.cheeky-fit.com/platform.json", "title": "The Platform | Four Layers | Cheeky-Fit", "headline": "Four layers, and what goes in.", "description": "The four layers Cheeky-Fit builds for every business: apps and websites, an API layer, an AI layer grounded in your records, and operations.", "language": "en-US", "dateModified": "2026-09-08", "image": "https://www.cheeky-fit.com/images/marketing/b2b-infra.webp", "publisher": { "@type": "Organization", "name": "Cheeky-Fit Inc.", "legalName": "Cheeky-Fit Inc.", "brand": "Cheeky", "url": "https://www.cheeky-fit.com/", "foundingDate": "2024", "location": "Manassas, Virginia, United States", "email": "jpande-cfo@cheeky-fit.com", "sameAs": [ "https://www.instagram.com/_cheeky.fit", "https://x.com/cheekyfit_", "https://www.youtube.com/@CheekyFitInc", "https://www.linkedin.com/company/cheeky-fit/", "https://www.pinterest.com/cheekyfit/", "https://mastodon.social/@cheekyfit", "https://open.spotify.com/show/4kIbMKoypVmPAHKrxvvvPb", "https://www.crunchbase.com/organization/cheekyfit", "https://medium.com/@CheekyFit" ] }, "app": { "name": "Cheeky", "tagline": "The AI fashion network", "categories": [ "lifestyle", "shopping", "social" ], "platforms": [ "iOS", "Android", "Web" ], "ios": { "url": "https://apps.apple.com/us/app/cheeky-fit-fashion/id6791432717", "appId": "6791432717", "bundleName": "Cheeky-Fit Fashion" }, "android": { "url": "https://play.google.com/store/apps/details?id=com.cheekyfit.app", "packageName": "com.cheekyfit.app" }, "price": "Free to download", "sellerCommission": "0%", "marketplaceReach": "22+ countries", "features": [ "Closet: AI wardrobe digitization and searchable clothing organization", "Styling: AI outfit recommendations and wardrobe gap analysis", "Social: real-outfit discovery through a fashion feed", "Marketplace: global fashion brands selling at 0% seller commission" ] }, "sections": [ { "heading": null, "text": "The same four layers; different contents every business." }, { "heading": "Four layers, and what goes in.", "level": 2, "text": "The same four layers under every build; what goes in them is the conversation." }, { "heading": "Built to the operation.", "level": 3, "text": "The screens people actually work in. iOS Android Web Internal dashboards Offline-tolerant" }, { "heading": "Your logic, made callable.", "level": 3, "text": "One source of truth for every app and agent. REST Webhooks Token auth Rate limits Versioned" }, { "heading": "Grounded in your records.", "level": 3, "text": "It reads your records first; a wrong answer is traceable. Retrieval Ingest pipelines Evaluation sets Guardrails Human review" }, { "heading": "The layer nobody buys.", "level": 3, "text": "Part of the engagement, not a second budget. Managed hosting CI / CD Monitoring Backups Patching" }, { "heading": "Application & device engineering", "level": 2, "text": "Native and web applications, the APIs behind them, and AI features built into the architecture rather than bolted on: for product teams, internal teams, and pilots that need to graduate to production. Native Android and iOS apps, and responsive web apps Internal tools and dashboards that replace re-keyed, manual workflows REST APIs, webhooks, auth, and integrations with your existing systems AI features on Vertex AI and Gemini: retrieval, evaluation, guardrails Pilots and prototypes engineered to become production software A working app or tool on production infrastructure, typically in weeks, with a deployment pipeline, monitoring, and an owner for the code after launch. We ship our own native Android app to Google Play today, from one API that also serves iOS and web." }, { "heading": "UX & product design", "level": 2, "text": "Research, flows, screens, and the front-end that implements them. One team, so nothing is lost between the design file and the code. User research, journey mapping, and flows built around how the work actually happens Platform-native interfaces: Material 3 and Apple HIG, dynamic color, type scale, accessibility Design systems and component libraries your product teams can reuse Clickable prototypes in days, ready to put in front of real users Front-end implementation on Android, iOS, and web, not just a handoff Screens that ship. Designed to the platform's guidelines and built by the same people, so the product your users see is the product that was designed. This site is one design system, designed, built, and run by the same team." }, { "heading": "Sales support", "level": 2, "text": "The data and tooling that sales and partner teams run on: cleaned, connected to the systems they already use, and reported in one place. Lead-generation and enrichment pipelines at scale, delivered CRM-ready CRM sync and data operations across Salesforce, HubSpot, Apollo, or custom systems Pipeline and partner dashboards with the metrics teams actually track Outreach tooling: sequences, templates, and automation with human review Pitch collateral, decks, and one-pagers for sales and partner conversations Sales and partner teams get clean data and working tools in the systems they already use, and a dashboard that reflects the pipeline as it is. We run our own outbound on this tooling: thousands of leads scraped, structured, enriched, and loaded into a CRM." }, { "heading": "Customer support", "level": 2, "text": "Support assistants and workflows grounded in your own documentation and records, evaluated before rollout and monitored after it. Retrieval-grounded assistants over your product docs, policies, and records Ticket triage, classification, and routing automation Evaluation harnesses and guardrails before anything reaches a customer Support dashboards and knowledge-base tooling for agents Monitoring with a route to a human when something breaks An assistant that answers from your data, not a general model guessing at your domain, with measured accuracy, escalation paths, and a team on call. The same retrieval, evaluation, and guardrail layers run in our own production AI pipelines today. Scroll to turn the page" }, { "heading": "Four layers, and what goes in.", "level": 1, "text": "Clients. Endpoints. The AI layer. Data and operations." } ], "faqs": [ { "question": "What are the four layers Cheeky-Fit builds?", "answer": "Clients, endpoints, intelligence, and foundation. Apps and websites on top, your business logic exposed as an API beneath them, an AI layer grounded in your records, and hosting, data, and operations underneath all of it." }, { "question": "What does the AI layer actually do?", "answer": "It reads your documents, history, and live records before answering, and cites which of them it used. A general model knows the world and nothing about your business; grounding is what makes an answer usable." }, { "question": "Do you train AI models on my company data?", "answer": "No. Retrieval runs against your records to answer your questions. Cheeky-Fit does not train shared or third-party models on one client's data. Details at cheeky-fit.com/security." }, { "question": "Which AI models do you use?", "answer": "Models are selected per workload and are swappable. The application talks to an interface rather than one vendor's SDK, so moving to a better or cheaper model is a change instead of a rewrite." }, { "question": "How do you know the AI is working?", "answer": "Every AI feature ships with a set of real cases from your business and a measured pass rate. Low-confidence outputs route to a person by default and automation expands as those numbers hold." }, { "question": "Can you work with the systems we already have?", "answer": "Yes. The endpoint layer is often built over existing systems so your website, staff tools, and partners read one source of truth instead of several drifting copies." }, { "question": "What platforms do you build apps for?", "answer": "iOS, Android, and web, plus internal dashboards and tools. A customer-facing surface and an internal one typically share a single backend so the two can never show contradictory numbers." }, { "question": "What is Cheeky-Fit not a good fit for?", "answer": "Anything an off-the-shelf subscription genuinely covers, staff augmentation sold by the seat, and procurement that requires a certified vendor on day one. Cheeky-Fit holds no compliance certifications today." }, { "question": "Do you hand over documentation?", "answer": "Yes. Source, infrastructure, and documentation land in your accounts, written so another team could pick the stack up. Terms are at cheeky-fit.com/engagements." }, { "question": "How is this different from hiring an agency?", "answer": "Engagements are scoped to a running system rather than to hours, you talk to the engineers writing the code, and the operations layer is part of the work instead of an upsell after it breaks." } ], "plainText": "The same four layers; different contents every business.\n\nFour layers, and what goes in.\nThe same four layers under every build; what goes in them is the conversation.\n\nBuilt to the operation.\nThe screens people actually work in. iOS Android Web Internal dashboards Offline-tolerant\n\nYour logic, made callable.\nOne source of truth for every app and agent. REST Webhooks Token auth Rate limits Versioned\n\nGrounded in your records.\nIt reads your records first; a wrong answer is traceable. Retrieval Ingest pipelines Evaluation sets Guardrails Human review\n\nThe layer nobody buys.\nPart of the engagement, not a second budget. Managed hosting CI / CD Monitoring Backups Patching\n\nApplication & device engineering\nNative and web applications, the APIs behind them, and AI features built into the architecture rather than bolted on: for product teams, internal teams, and pilots that need to graduate to production. Native Android and iOS apps, and responsive web apps Internal tools and dashboards that replace re-keyed, manual workflows REST APIs, webhooks, auth, and integrations with your existing systems AI features on Vertex AI and Gemini: retrieval, evaluation, guardrails Pilots and prototypes engineered to become production software A working app or tool on production infrastructure, typically in weeks, with a deployment pipeline, monitoring, and an owner for the code after launch. We ship our own native Android app to Google Play today, from one API that also serves iOS and web.\n\nUX & product design\nResearch, flows, screens, and the front-end that implements them. One team, so nothing is lost between the design file and the code. User research, journey mapping, and flows built around how the work actually happens Platform-native interfaces: Material 3 and Apple HIG, dynamic color, type scale, accessibility Design systems and component libraries your product teams can reuse Clickable prototypes in days, ready to put in front of real users Front-end implementation on Android, iOS, and web, not just a handoff Screens that ship. Designed to the platform's guidelines and built by the same people, so the product your users see is the product that was designed. This site is one design system, designed, built, and run by the same team.\n\nSales support\nThe data and tooling that sales and partner teams run on: cleaned, connected to the systems they already use, and reported in one place. Lead-generation and enrichment pipelines at scale, delivered CRM-ready CRM sync and data operations across Salesforce, HubSpot, Apollo, or custom systems Pipeline and partner dashboards with the metrics teams actually track Outreach tooling: sequences, templates, and automation with human review Pitch collateral, decks, and one-pagers for sales and partner conversations Sales and partner teams get clean data and working tools in the systems they already use, and a dashboard that reflects the pipeline as it is. We run our own outbound on this tooling: thousands of leads scraped, structured, enriched, and loaded into a CRM.\n\nCustomer support\nSupport assistants and workflows grounded in your own documentation and records, evaluated before rollout and monitored after it. Retrieval-grounded assistants over your product docs, policies, and records Ticket triage, classification, and routing automation Evaluation harnesses and guardrails before anything reaches a customer Support dashboards and knowledge-base tooling for agents Monitoring with a route to a human when something breaks An assistant that answers from your data, not a general model guessing at your domain, with measured accuracy, escalation paths, and a team on call. The same retrieval, evaluation, and guardrail layers run in our own production AI pipelines today. Scroll to turn the page\n\nFour layers, and what goes in.\nClients. Endpoints. The AI layer. 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