Ready-Made AI Platform for Resellers
A typical request: a reseller wants to sell AI content generation to their clients but lacks the infrastructure. The "from scratch" option means 12–18 months of development and a team of 10+ specialists. Our team has been developing AI platforms for resellers and has accumulated over 30 successful cases. We provide a white-label AI platform, ready for customization under the customer's brand. In 20 weeks, you get a production-ready system with multi-tenant architecture: isolated data, an AI gateway supporting GPT-4o, Claude, Llama 3, Stable Diffusion, and Whisper, billing through Stripe, and a custom UI. Over 30 successful AI projects confirm the reliability of the approach. Request a demo access to evaluate the capabilities.
How Multi-Tenant AI Architecture Works
Each tenant operates in its own context: separate vector databases (ChromaDB, Qdrant, pgvector), prompt libraries, and optionally fine-tuned models. Data-level isolation ensures client information never crosses. Tenant-specific domains (CNAME + SSL) are connected automatically. The system handles up to 1000 RPS per tenant with p99 latency under 500 ms. The multi-tenancy concept is implemented following best practices from Wikipedia.
What's Included in the White-Label Platform
Core AI Functions
- White-label text generation (LLM: GPT-4o / Claude / Llama 3 — configurable)
- AI image generation (Stable Diffusion XL / DALL·E 3 — configurable)
- TTS / STT (ElevenLabs / Whisper)
- Extensible module set via plugin architecture
Multi-Tenant Infrastructure
- Data isolation at tenant level (separate vector stores, prompt libraries, fine-tuning models)
- Custom domain per tenant (CNAME + SSL)
- White-label branding: logo, colors, name in UI and email notifications
Billing & Quota
- AI platform billing via Stripe integration for subscription management
- Flexible tariff plans with limits on tokens/images/TTS minutes
- Overage billing
- Reseller margin control (platform → reseller → end customer, each level its own prices)
Admin Panel
- Tenant, user, and quota management
- Usage analytics per tenant
- Model configuration per plan
Why a White-Label Platform Beats In-House Development
Compare: in-house development requires hiring 8–12 developers (ML, backend, frontend, DevOps) for a year. A white-label platform is ready in 20 weeks with a team of 3–4 engineers. Meanwhile, you get code that has already passed load testing and a security audit. According to our data, time-to-market increases by 5–10 times, and budget savings reach 70%.
| Parameter | In-house | White-label |
|---|---|---|
| Time to launch | 12–18 months | 20 weeks |
| Team size | 8–12 people | 3–4 people |
| Initial investment | from $50,000 | individual |
| Risks | high | low (proven code) |
Additional performance comparison:
| Metric | White-label | Typical in-house |
|---|---|---|
| RPS per tenant | up to 1000 | up to 200 |
| p99 latency | < 500 ms | 1–2 sec |
| Time per feature | 1–2 days | 1–2 weeks |
Technical Architecture
Backend: Node.js / FastAPI + PostgreSQL (tenant data) + Redis (rate limiting, session) + S3 (generated assets). Docker + Kubernetes for scaling.
Frontend: React + Next.js, fully customizable themes via CSS variables. Component system to enable/disable features per plan.
AI Gateway: a custom proxy layer between the platform and AI providers. It provides: rate limiting, cost tracking, fallback between providers, prompt injection protection. Routing via Envoy with weighted round-robin, prompt injection detection based on regex and an ML model. We measure p99 latency for each provider and switch if a threshold is exceeded. LLM API for resellers is available through the AI Gateway.
API: OpenAPI spec, SDKs for JavaScript and Python, webhook support for integrations.
Development Process
- Analytics and design (2 weeks): define requirements for AI modules, tenant isolation, billing.
- Core system (4 weeks): multi-tenancy, auth, basic AI gateway.
- Billing and admin panel (4 weeks): Stripe integration, quota management, usage tracking.
- White-label UI (3 weeks): branding, themes, custom domain.
- Integrations and SDK (2 weeks): OpenAPI, webhook, client SDKs.
- Testing and deployment (3 weeks): load testing, security audit, CI/CD.
- Documentation and onboarding (2 weeks): reseller guides, onboarding flow.
Total: 20 weeks to production.
Compliance and Security
GDPR data processing agreements at the tenant level. Optional self-hosted deployment for clients with data residency requirements. Rate limiting at all levels. Prompt injection protection in the AI gateway. RBAC for multi-user tenant accounts.
With 5 years of experience building AI platforms and over 30 delivered projects, we guarantee stable operation under load up to 1000 RPS per tenant. Order development or get a consultation — we'll evaluate your project for free. Get demo access to see the architecture in action.