Modular Pipeline Core
Decompose monolithic agent flows into composable, testable modules with explicit contracts and versioned schemas.
AI Infrastructure · 2026
The core engine for autonomous AI workflows
Tegore AI deconstructs complex automation pipelines into intuitive modular cores — with real-time semantic retrieval debugging, multimodal agent network monitoring, and end-to-end token optimization.
99.9%
Pipeline uptime
-42%
Token spend
<50ms
Trace latency
12 agents · 3 pipelines active
Trusted by engineering teams building production-grade LLM systems
NEXUS
VERTEX
ORBITAL
PRISM
AXIOM
Core Capabilities
Precision orchestration, zero clutter
Every module is designed for deterministic behavior at enterprise scale.
Semantic Retrieval Debug
Inspect embedding drift, reranker scores, and retrieval paths in real time — before bad context reaches your agents.
Agent Network Monitor
Visualize multimodal agent handoffs, tool invocations, and failure cascades across your entire workflow graph.
Token Optimization
Automatic prompt compression, cache-aware routing, and spend attribution per pipeline, tenant, and model.
Deterministic Guardrails
Policy-as-code enforcement with audit trails. Ship agent workflows that behave predictably under load.
Developer-First SDK
TypeScript and Python SDKs with local emulation, CI-friendly snapshots, and OpenTelemetry-native tracing.
Architecture
Built for the full agent lifecycle
From prototype to production — Tegore AI gives you observability and control at every layer of your stack.
- Ingest → Retrieve → Reason → Act → Audit
- Multi-tenant isolation with per-workflow quotas
- Deploy on Cloudflare, AWS, or self-hosted
// pipeline.config.ts
export default definePipeline({
name: 'customer-support',
agents: ['router', 'retriever', 'responder'],
guardrails: { maxTokens: 4096, pii: 'strict' },
trace: { sampleRate: 1.0, export: 'otlp' },
})
Ready to orchestrate with certainty?
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