ESTABLISHED 2023. BASED IN USA.

PRODUCTION AI
INFERENCE
INFRA.

Geodd is an infrastructure platform focused on running AI inference systems in production with stable latency, predictable throughput, and continuous operational support.

Observed Uptime
~99.99%
Continuous production stability
Global GPU Fleet
500+
H200, H100, Pro 6000 capacity
Active Regions
Multi
US-East, US-Central, US-West
Concurrency
128+
Stable requests per instance

System Boundaries
& Responsibility.

Geodd operates the full inference lifecycle or specific infrastructure layers depending on deployment type. Responsibility is defined at the system boundary.

Active
API_v2.0

Managed Inferencing

Geodd Handles
Deployment, runtime, scaling, monitoring, debugging
Customer Handles
Application layer ownership
Active
DED_v4.1

Dedicated Inferencing

Geodd Handles
Infrastructure, orchestration, stability
Customer Handles
Model + system behavior ownership
Active
RAW_v1.2

Dedicated GPUs

Geodd Handles
Hardware only (Bare Metal)
Customer Handles
Full stack ownership

Vertically Integrated
Performance Stack.

The system is structured as a vertically integrated stack where deployment, execution, and operations are tightly coupled to maintain predictable behavior under load.

ORCH_v2.0
01

DeployPad

Workload-driven orchestration, infrastructure selection, and cost optimization.

EXEC_v4.1
02

Optimised Model Engine

Graph-level optimization and speculative decoding (2–3× token speed).

OPS_v1.2
03

MLOps Services

Continuous monitoring, performance tuning, and failure recovery.

Reliability Model
System Behavior.

Systems are designed to remain stable under sustained load and to recover quickly when failure conditions occur.

Live Monitor
REF_UPTIME_99.99
Infrastructure-Level Availability
99.99%

Observed stability maintained at the infrastructure layer through redundant power, networking, and hardware-level fault handling.

Redundant Systems
Real-Time Detection
No Escalation
DC-REGION: US-CENTRAL-01
OperationalLoad: 42.4%
Failure Protocol
01

Alerting

Engineers responsible for the system are alerted directly via real-time diagnostics.

02

Diagnosis

Infra + MLOps teams act together without ticket routing or intermediate layers.

03

Resolution

Continuous performance tuning and optimization are applied without user intervention.

Engineering-Led
System Ownership.

Systems are built and operated by the same engineering group. There is no separation between development and production ownership.

Unified Team

No handoffs between teams. Engineers manage the production systems they build.

Direct Context

Decisions based on real-time usage patterns and deep system proximity.

Interaction Model

Direct Access to Engineers

Interaction happens directly with engineers responsible for the system. There are no intermediate support layers or escalation chains.

Direct communication (Slack, WhatsApp, etc.)
End-to-end ownership per issue
Production incident handling by operators
Ready to scale?

Build on production-grade infrastructure

Experience stable latency and predictable throughput with our optimized inference platform.