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FlotorchAI

FlotorchAI delivers a single LLM gateway and control plane that lets teams onboard multiple models, route traffic by cost & latency, and govern GenAI apps from pilot to production.
unified LLM gatewaymulti-model routingenterprise AI gatewayRAG production pipelineLLMOps platformmodel access controlLLM cost & latency monitoring

Features of FlotorchAI

One API to call every model and agent framework—no more interface sprawl.
Bring your own fine-tuned models or plug MCP servers straight in.
Smart routing by cost, latency or schedule; switch models on the fly.
No-code A/B lab to benchmark agents, models and prompts side-by-side.
Track tokens, latency, relevance and context accuracy in one dashboard.
End-to-end RAG toolkit: chunking, embeddings, retrieval tuning & more.
Built-in guardrails, observability, prompt library and multi-tenant workspaces.
Full LLMOps loop from data to API to app for continuous iteration.

Use Cases of FlotorchAI

Centralize access control when your org uses multiple model vendors.
Run head-to-head model tests before go-live without writing code.
Balance cost vs. speed during traffic spikes with dynamic routing.
Design and optimize retrieval-augmented apps with turnkey RAG tooling.
Isolate projects and share prompts safely across distributed teams.
Monitor token burn, request volume and $/query for finance & ops.
Migrate legacy apps to the gateway with zero-code compatibility layer.

FAQ about FlotorchAI

QWhat is FlotorchAI?

A unified LLM/Agent gateway that exposes one endpoint for every model and adds routing, evaluation and governance out of the box.

QWhich model types can FlotorchAI connect to?

Any LLM, fine-tuned variant, agent framework or MCP server—bring your own or use the built-in catalog.

QWhat problem does the routing engine solve?

It automatically sends each request to the cheapest or fastest model based on rules you set—cost, latency or time-of-day.

QDoes FlotorchAI support RAG?

Yes. It covers the entire RAG pipeline: preprocessing, chunking, embeddings, vector stores and retrieval tuning.

QIs there an evaluation or testing feature?

Yes. A no-code lab lets you compare models, agents and prompts on relevance, latency and cost before production.

QWhat governance and security features are included?

Observability, RBAC, guardrails, centralized secrets and workspace isolation for compliant multi-team development.

QHow can I deploy FlotorchAI?

Cloud-hosted SaaS or self-hosted in your VPC—contact the team for exact availability.

QIs pricing publicly listed?

No public pricing was found; reach out to FlotorchAI for current plans and volume discounts.

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