Hybrid AI Deployment
The Best of Both Worlds
Send heavy reasoning to frontier models. Keep sensitive data on local models. One orchestration layer that finds the optimal balance between privacy, capability, and cost � automatically, on every request.
Hardware racked, networked, and validated by Remote Hand engineers; integration overseen by Expert Now IP-network and Linux specialists. Pay-as-you-go across 30+ US cities.
The Trade-Off We Solve
Frontier models � Claude, ChatGPT, Gemini � are unmatched on hard reasoning, multimodality, and long context. But they live in someone else’s data center. Local models are private, fast, and cheap, but they can’t yet match frontier capability on the hardest tasks. You shouldn’t have to choose. With Hybrid AI, you don’t.
Public Lane
Frontier capability on demand
Strategic analysis, deep code refactoring, multimodal reasoning, 200K+ token contexts. Routed to Claude, ChatGPT, or Gemini under enterprise terms � only after policy and PII checks have approved the payload.
Private Lane
Sensitive work, on your own metal
PII, financials, medical notes, employee data, source code � handled by tuned small language models running on your own hardware. Nothing leaves the network, ever.
How the Router Works
Every Request Takes the Right Lane
A lightweight router sits between your users and the model fleet. It classifies, redacts, decides, and audits � in milliseconds.
01
Classify
A small classifier scores task complexity and detects sensitive entities � names, account numbers, medical codes, contract clauses.
02
Apply Policy
Your rules decide. Block, allow, or pseudonymize. Mask the customer ID, send the structure. Different policies per team, per project, per data class.
03
Route
Simple, sensitive requests stay on the local model. Complex, non-sensitive ones go to the frontier. Mixed tasks split � local handles redaction, frontier handles reasoning.
04
Audit
Every routing decision is logged with the policy that triggered it. Searchable, exportable, ready for your compliance reviewer.
A Real Example
Your sales rep asks: “Summarize the latest contract from Acme Corp and draft a follow-up that addresses their concerns.”
Step 1 � Local
The local model fetches the contract from your CRM, extracts entities, and tokenizes party names, dollar amounts, and clause IDs.
Step 2 � Frontier
A redacted version with placeholders goes to Claude or ChatGPT for the heavy reasoning � summarization, objection handling, persuasive draft.
Step 3 � Local
Placeholders are rehydrated locally with the real names and figures, then the rep gets a finished draft. The frontier never saw the customer’s name.
What You Get
Capability Without Compromise
Frontier-grade output on every task that doesn’t touch sensitive data. Local-grade privacy on every task that does. No team has to choose, no policy has to be bent.
Lower Total Cost
Most everyday tasks � classification, extraction, formatting, simple Q&A � never need a frontier model. Routing them locally cuts API spend by 60�90% in typical SMB deployments.
Provider Independence
Swap Claude for Gemini for ChatGPT � or all three � without rewriting a line of application code. The router treats them as interchangeable backends.