ElectriPy Platform
The infrastructure layer for production AI.
Models, agents, workflows, RAG systems, and tools run on top of the runtime. ElectriPy provides six capability domains covering everything required between prototype and production.
Capability Domain
Reliability
Never leave production to chance.
The Problem
AI systems fail in production. Models return errors. Providers go down. Rate limits are hit. Without explicit reliability infrastructure, every failure is a manual intervention.
What ElectriPy Delivers
Circuit breakers, retries with backoff, timeout propagation, rate limiting, and fallback routing built directly into the execution path — not bolted on after incidents.
Runtime Components
Applied To
- High-availability agent systems
- Multi-provider LLM routing with fallback
- Workloads with strict latency SLAs
Capability Domain
Observability
AI systems should not be black boxes.
The Problem
Without structured observability, you cannot diagnose failures, measure performance, track costs, or understand what agents actually did. Logging is not observability.
What ElectriPy Delivers
Structured traces with span-level visibility, OpenTelemetry export, automatic PII redaction, session context, and token and cost metadata — instrumented at every workload boundary.
Runtime Components
Applied To
- Production trace pipelines
- Compliance-sensitive systems requiring PII redaction
- Cost and token attribution per request
Capability Domain
Governance
Runtime enforcement, not documentation.
The Problem
AI systems make consequential decisions. Without runtime governance, there is no way to enforce policies, require approvals, maintain audit trails, or prove compliance to auditors.
What ElectriPy Delivers
Runtime policy engine with typed decisions, action gating, configurable approval workflows, evidence requirements, and structured audit trails — built into the execution path.
Runtime Components
Applied To
- Regulated industries requiring audit trails
- Human-in-the-loop approval workflows
- High-stakes autonomous agent actions
Capability Domain
Orchestration
Composable, typed, testable primitives.
The Problem
Production AI involves routing, realtime sessions, tool composition, and skill execution. Doing this ad hoc produces brittle, untestable orchestration code that breaks at scale.
What ElectriPy Delivers
Router, realtime session orchestration, MCP integration, and versioned skills packaging — composable orchestration primitives with typed APIs and no hidden execution model.
Runtime Components
Applied To
- Multi-model routing with capability matching
- Streaming agent sessions with interruption support
- Tool-augmented agents with MCP
Capability Domain
Evaluation
Catch regressions before they reach production.
The Problem
AI systems degrade silently. Without systematic evaluation and regression gates, quality drops are discovered in production by customers, not in CI by engineers.
What ElectriPy Delivers
Evaluation framework with pluggable scorers, baseline comparisons, regression reporting, and CI-friendly quality gates that run in your pipeline before every deployment.
Runtime Components
Applied To
- RAG pipeline quality regression prevention
- Pre-deployment evaluation gates in CI
- Continuous quality monitoring
Capability Domain
Model Runtime
Provider-agnostic from day one.
The Problem
Provider lock-in and absent structured output handling are common failure points. Hard-coded provider integrations create maintenance debt and block migration.
What ElectriPy Delivers
LLM Gateway with clean provider abstraction, structured output engine, and swap seams designed for provider migration without application rewrites.
Runtime Components
Applied To
- Multi-provider production systems
- Structured output extraction pipelines
- Provider migration without application rewrites
Get Started
Six domains. One runtime. Open source.
Install ElectriPy and adopt the capabilities your system needs today. Expand incrementally as production requirements evolve.