Custom CRM frontends
A CRM surface built around how your team actually sells and services, on top of the data you already hold, instead of bending the business to fit a generic tool.
Explore custom crm frontends
Pillar three
We build application frontends. Real state management, real data, real speed, server rendered so search engines and AI crawlers see everything on the first request. The same architecture behind SpinFlow.ai, our enterprise AI platform.
What this is
Most company sites are a slideshow with a contact form bolted to the end. That was fine when the site was a brochure. It is not fine when the site is the product surface.
A brochure page has one move: convince someone to call. An application frontend can quote a job, take a booking, show an account, run a configurator, or hand a customer their own data. Those interactions carry the revenue that a paragraph of copy only points at.
The catch is that most interactive work gets built in a way that hides it. Content that only appears after a JavaScript bundle executes is content a crawler may never read, and an answer engine almost certainly will not. So teams end up choosing between a site that converts and a site that gets found.
Server rendering settles that. The HTML arrives complete on the first request, so users see text instead of a spinner and crawlers see the page instead of an empty shell. The interactivity hydrates on top. You get both, from one codebase, with one deployment.
This is the same architecture we run behind SpinFlow.ai, our enterprise AI platform. We did not invent a lighter version for client work. Clients get the platform stack.
What is inside
Each of these ships server rendered, typed, and instrumented from the first deploy.
A CRM surface built around how your team actually sells and services, on top of the data you already hold, instead of bending the business to fit a generic tool.
Explore custom crm frontendsOperational and analytics dashboards with role-scoped views and live data, designed so people open them daily rather than ignore them.
Explore dashboardsAuthenticated client-facing surfaces for documents, status, and history, with row-level security enforced in the database.
Explore client portalsTooling that retires the spreadsheet and the manual handoff, scoped tightly enough to ship instead of sprawl.
Explore internal toolsOnboarding, billing surfaces, and feature gating for a product, sharing one design system with the marketing site.
Explore saas frontendsMoves off a static or page-builder site with URL mapping, full 301 coverage, and a measured baseline so the rebuild can be proven.
Explore migration from staticOur own enterprise AI platform, running the architecture we sell. We point at a live system instead of a portfolio screenshot.
Explore spinflow.ai, the proofHow we run it
Five phases. Nothing gets styled before the architecture is settled, because that order is what keeps the cost down.
What the frontend has to do, who uses it, what systems it touches, and every URL that already exists and carries equity.
Rendering strategy per route, data layer, auth boundaries, and the design token system. Written down and agreed before code.
Marketing routes and application routes in one codebase, server rendered by default, typed end to end, mobile first from 375 pixels up.
Redirect map with no chains or orphans, analytics and Search Console verified before go live, and a performance baseline captured.
Post-launch monitoring against the baseline, then continuous shipping. The platform keeps growing instead of freezing at launch.
A website presents information. An application frontend performs work: it holds state, reads and writes real data, authenticates users, and renders on the server so both people and crawlers get the full page on the first request. It is software architecture rather than assembled page-builder blocks.
Cross-pillar
Almost every other program in this shop performs better or worse depending on what happens here.
Rendering strategy is the single biggest technical constraint on organic growth, which is why this pillar and SEO are usually scoped together rather than in sequence.
Assistant crawlers frequently do not execute JavaScript at all, so server rendering is a hard prerequisite for AEO and not an optimization applied afterwards.
Agents, internal tools, and automated workflows need a real interface to live in, which is what the surfaces built under AI and automation plug into.
Tokens, components, and interaction patterns come out of design as code rather than as a static file handed over the wall.
Events, conversions, and dashboards get wired during the build by analytics so measurement is never a retrofit after launch.
Questions
Server rendered, measurable, and yours to keep.