40-80%
typical savings vs. direct provider pricing
The same SDK setup, lower cost
Keep your OpenAI-compatible client. The core change is usually a base URL swap, not a rebuild — so your existing client work keeps running.
InferencePartners
Protect the margin on every AI agent you build.
InferenceSaver gives AI agencies a cheaper OpenAI-compatible model layer for client chatbots, agents, RAG systems, and workflow automations. Same build, lower inference cost.
Same client build. Lower runtime cost.
You already ship the AI work. We sit underneath it as the model layer, so usage growth improves your margin instead of eating it.
What agencies get
A cheaper runtime layer that keeps your SDK setup, your models, and your client relationships intact.
1
endpoint for every model you resell
Every major model, one layer
Route across every provider we support from a single endpoint. Swap models per client without stitching together separate accounts.
24/7
routing across supported providers
Deposit-tier discounts
The more you fund upfront, the lower each call costs. Turn inference into a margin lever on every retainer and fixed-fee project.
Zero
data retention on inference calls
Zero data retention
End-to-end encryption and zero retention on every call. Your clients' prompts and completions never train third-party models.
40-80%
typical savings vs. direct provider pricing
The same SDK setup, lower cost
Keep your OpenAI-compatible client. The core change is usually a base URL swap, not a rebuild — so your existing client work keeps running.
1
endpoint for every model you resell
Every major model, one layer
Route across every provider we support from a single endpoint. Swap models per client without stitching together separate accounts.
24/7
routing across supported providers
Deposit-tier discounts
The more you fund upfront, the lower each call costs. Turn inference into a margin lever on every retainer and fixed-fee project.
Zero
data retention on inference calls
Zero data retention
End-to-end encryption and zero retention on every call. Your clients' prompts and completions never train third-party models.
40-80%
typical savings vs. direct provider pricing
The same SDK setup, lower cost
Keep your OpenAI-compatible client. The core change is usually a base URL swap, not a rebuild — so your existing client work keeps running.
1
endpoint for every model you resell
Every major model, one layer
Route across every provider we support from a single endpoint. Swap models per client without stitching together separate accounts.
24/7
routing across supported providers
Deposit-tier discounts
The more you fund upfront, the lower each call costs. Turn inference into a margin lever on every retainer and fixed-fee project.
Zero
data retention on inference calls
Zero data retention
End-to-end encryption and zero retention on every call. Your clients' prompts and completions never train third-party models.
40-80%
typical savings vs. direct provider pricing
The same SDK setup, lower cost
Keep your OpenAI-compatible client. The core change is usually a base URL swap, not a rebuild — so your existing client work keeps running.
1
endpoint for every model you resell
Every major model, one layer
Route across every provider we support from a single endpoint. Swap models per client without stitching together separate accounts.
24/7
routing across supported providers
Deposit-tier discounts
The more you fund upfront, the lower each call costs. Turn inference into a margin lever on every retainer and fixed-fee project.
Zero
data retention on inference calls
Zero data retention
End-to-end encryption and zero retention on every call. Your clients' prompts and completions never train third-party models.
Why it works differently.
Client AI projects get less profitable as token usage grows. InferenceSaver turns that variable cost into a margin lever you control.
Margin recovery on every build
When a client's AI usage grows, your provider bill grows with it. Route through us and keep more of every retainer and fixed-fee project.
OpenAI-compatible, no rewrite
If your build already uses an OpenAI-compatible client, the migration is usually a base URL change — not a re-architecture.
One runtime for every client
Manage inference for all your client projects through a single endpoint and deposit balance instead of juggling provider accounts.
A cleaner client proposal
Add an AI runtime cost line that shrinks over time. Give clients cheaper inference while you protect your own margin.
Who it fits
Built for teams shipping AI implementation work for clients — not generic web shops with an AI add-on.
- You build client-facing AIChatbot & agent studios
You build client-facing AI
Chatbot & agent studios
You ship customer support agents, AI receptionists, and voice or chat assistants for clients calling OpenAI, Anthropic, or Gemini directly.
- You wire AI into operationsAutomation & workflow agencies
You wire AI into operations
Automation & workflow agencies
You build n8n, Make, or Zapier AI workflows and CRM/ERP integrations where model usage — and its cost — scales with the client.
- You deliver production AIRAG & implementation consultants
You deliver production AI
RAG & implementation consultants
You stand up RAG and knowledge systems for clients and need a cheaper, reliable model layer with zero retention and provider flexibility.
Send us one client workflow.
Share a typical client workflow or your current model mix and monthly spend. We'll show what it would cost through InferenceSaver and the base URL swap — before you change anything.
Who you'll be working with
The team building websites, AI systems, and the operational layer that helps businesses launch and run better with InferenceSaver.
Ethan
Engineering & Support
Engineering, product surfaces, and builder support
Can't decide if we're the right choice?
Ask the AI assistant you already trust about InferenceSaver and get an independent comparison.
Still got questions? Ask your favourite AI if InferenceSaver makes sense for you.
Get in touch with our team
Book a demo to discover how InferenceSaver can improve your AI operations, model costs, and production workflows.
“We finally have an AI stack that the product and engineering teams can use without switching between providers.”
Priya Nair
AI Operations Lead
Up to 2x usage throughput on the same spend
400ms median time to first response from frontier models
60-80% lower inference costs without sacrificing latency
We will map your current setup, recommend the right plan, and show a clear path to rollout.