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react and next.js front-ends

React and Next.js front-ends for production AI features.

Gaper builds React and Next.js product UIs and the front-ends that put AI agents in front of real users: chat surfaces, streaming responses, approval screens, and dashboards. We ship the interface wired to your agent, your data, and your auth, then hand over the code.

Book a free AI assessmentWhat is an AI agent?
Map the workflowBuild the supervised agentSandbox, verify, go live
gaper · agent runtime
$ gaper deploy agent --to production
✓ plan ……………… 4 steps
✓ retrieve …… 1,240 docs grounded
✓ tool ………… salesforce.update_record
✓ eval ………… 12/12 checks passed
● live · p95 1.2s · 0 errors
● in productionowned by your team
In one sentence

A React and Next.js front-end is the production interface layer for a web product or AI feature: components, routing, server rendering, and state, wired to live APIs and auth. Gaper builds these UIs, including agent chat surfaces and dashboards, and deploys them in your stack for your team to own.

ProductionNot another demo
Model-agnostic
In your cloudYour auth, your data
You own itCode, evals, runbook
Why this matters

Most AI features stall at the interface. The model works in a notebook, but there is no production UI that streams responses, shows citations, gates risky actions, and holds up under real traffic. That front-end is the part users actually touch, and it is the part most projects never finish.

Production filter
  • Does it touch real systems?
  • Can the outcome be measured?
  • Where does human approval stay?
  • Who owns it after launch?
Free AI assessment

Book a free assessment. We will identify one high-leverage workflow, make the build-vs-buy call, and scope the smallest production release.

Map your first production agent
How we work

From strategy to production, owned by your team.

  1. 01

    Map the workflow

    We start from the documents, SOPs, portals, inboxes, and spreadsheets your team already uses, then turn the repeatable path into an agent workflow map.

  2. 02

    Build the supervised agent

    We build on OpenAI, Claude, Gemini, or the right model for the job, with evals, guardrails, citations, and human approval gates where risk matters.

  3. 03

    Connect the stack

    The agent gets the data layer, APIs, MCP tools, auth, and write-backs it needs to finish work inside your systems, not beside them.

  4. 04

    Sandbox, verify, go live

    We launch in a sandbox, verify every run, then move into supervised production with traces, rollback, and an owner.

What we build

Agents wired into the systems you already run.

Product UIs in React

Component-driven interfaces built in React and TypeScript: forms, tables, flows, and dashboards that match your design system and ship to production.

Next.js app architecture

App Router, server components, server actions, and edge or node rendering chosen per route, so pages stay fast and SEO holds up.

AI feature front-ends

Chat surfaces, streaming token UIs, tool-call states, citation displays, and approval screens that put a supervised agent in front of real users.

Agent and API integration

The UI wired to your agent, your APIs, and MCP tools, with auth, optimistic updates, and error and retry states handled cleanly.

Design system and accessibility

Reusable component libraries, responsive layouts, and WCAG-conscious markup so the interface scales across teams and devices.

Performance and observability

Core Web Vitals budgets, code splitting, and front-end telemetry so you can see load, errors, and usage in production, not guess.

Built into production, not bolted on

We deploy the front-end where your product lives: your cloud, your auth, your CI. The UI inherits your security posture and ships through your release process instead of living as a separate demo.

  • Runs in your environment or ours
  • SSO, RBAC, and session handling wired in
  • No data retention you didn't ask for
Deploy target
OpenAIOpenAIClaudeClaudeGeminiGeminiSalesforceSalesforceSnowflakeSnowflakePostgresPostgres
SSORBACAudit logCloud

You own the interface, and the code

A forward-deployed team works alongside yours and hands over a clean React and Next.js codebase you fully control. No black box, no proprietary widget you can only edit through us.

  • Documented, typed component code
  • Knowledge transfer built into delivery
  • Extend and restyle it without us
Handover state
handoff packageCode, runbook, evals, dashboard
owned by your team
Source repoRunbookEval suiteOwner training

Access your auth

Data your environment

Ops monitor or handoff

The AI feature surface most teams never finish

The hard part of an AI feature is the interface: streaming, partial output, tool states, citations, and human approval on risky actions. We build that surface against your real agent, verified in a sandbox before users see it.

  • Streaming and tool-call UI states
  • Approval gates on consequential actions
  • Verified in sandbox before go-live
Release gate
  1. 01Eval suiteknown + edge casespass
  2. 02Policy checkguardrails enforcedpass
  3. 03Human fallbacklow-confidence routedhold
  4. 04Releaseshipped to prodlive

p95 latency 1.2s

eval pass 12/12

rollback ready

Model and stack agnostic
OpenAIClaudeGeminiLangChainMCPPythonTypeScriptPinecone
FAQ

Questions buyers ask us.

What kind of front-ends does Gaper build?+
Production React and Next.js interfaces: product UIs, dashboards, and the front-ends for AI features such as agent chat, streaming responses, citation views, and approval screens. We build the interface and wire it to your agent, APIs, and auth.
How do you deploy the front-end into our stack?+
We ship through your CI into your cloud and hosting, behind your auth and SSO. The UI runs alongside your existing product and release process. For scoped builds a first working interface can land in as little as 24 hours.
Who owns the code after launch?+
You do. We hand over a clean, typed, documented React and Next.js codebase with knowledge transfer built into delivery, so your team can extend, restyle, and maintain it without us. No lock-in.
Which AI models can the front-end connect to?+
Any of them. The UI is model-agnostic and talks to your agent layer on OpenAI, Claude, Gemini, or open models, integrated through your APIs and MCP tools, so the interface does not change when the model does.
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Ready to deploy your first agent?

Book a free 30-minute assessment. We'll map the highest-leverage workflow and scope the smallest thing worth shipping, live in as little as 24 hours.

Build, deploy, runYour cloudYou own the code