Deploy GPU applications on supported community hardware and cloud capacity
The Context Gateway for AI systems
Stage
Startup
Not given
Founded
2026
Not given
Based in
SA
CH
Pricing model
Paid
Freemium
Pricing
One published price per GPU model in USD per GPU-hour. Hosts keep 90% of completed rental fees and Petabyte keeps 10%. A reservation holds funds, with final charges and returned balance following settlement after the run completes.
Community: Free (open-source, local use). Pro: $9/month or $90/year (personal cloud sync, 1 GB hosted index). Team: $29/month per seat or $290/year per seat (team server, shared workspace, 20 GB index, 1-25 seats). Enterprise: Contact for pricing.
Key features
Choose from available GPU hardware with published hourly rates
Review cost estimates before deployment starts
Start from ready-made template applications
Monitor workload lifecycle states, logs and outputs
Connect your own GPU hardware as a host
Escrow-based payment system for secure transactions
Support for inference model requests
Source selection and retrieval with task-relevant context at configurable depth
Access controls via PathJail boundary enforcement and role-based permissions
Read-time content filters for injection patterns and personal data detection
Memory and continuity to retain findings and connections across sessions
Evidence and outcomes recording with source references and usage audit trails
Integration with AI tools via SDK, MCP, hooks and supported client adapters
Local, VPC, on-premises and offline deployment options
Optional production intelligence for planning, ranking and routing enhancements
SDK with five stable primitives and six Agent Tools language contracts
Context cache, reference routing and usage accounting
What makes it different
Escrow payment ensures work is delivered before host is paid
Transparent pricing: all rates published upfront with no surprises
Minimal transaction fees: hosts keep 90% of rental earnings
Automatic refunds for failed rentals on platform side
Deterministic, model-agnostic context processing independent of AI provider choice
Governs context without controlling model calls, keeping AI decisions under user ownership
Records measurable impact with 64.1% reported context reduction in field use
Open-source core (Apache 2.0) with commercial tiers for teams and enterprises
Transparent governance with separate evaluation of task outcome from context delivery
LeanCTX