weaveIntel is the AI runtime that threads governance, orchestration, and observability into every agent interaction — so you ship faster without losing control.
25 Capabilities · 5 Themes
From orchestration to governance, connectivity to scale — weaveIntel provides a complete runtime for production AI systems.
Build complex multi-agent pipelines with deterministic control flow, automatic retries, and real-time observability.
Loom Engine · Skill Router · Memory Fabric · Context Window Manager · Agent LifecycleEvery token passes through configurable policy gates. PII detection, content filtering, and audit trails come standard.
Policy Engine · PII Detection · Audit & Lineage · Role-Based Access · Content SafetyUnified adapter layer for OpenAI, Anthropic, Google, Cohere, local models, databases, APIs, and file systems.
Model Gateway · Tool Framework · Data Connectors · Vector Search · Event BusHorizontal scaling, intelligent caching, cost tracking, and performance analytics built into the runtime.
Auto-Scaling · Semantic Cache · Cost Analytics · Performance Monitor · Load BalancerExtend weaveIntel with custom skills, adapters, policies, and UI components. Everything is a plugin.
Skill SDK · Custom Policies · UI Components · Webhook System · Extension RegistryBuilt with weaveIntel
A production reference app showing how weaveIntel powers complex, regulated AI in healthcare genomics.
geneWeave processes VCF files, annotates variants against ClinVar, and generates clinical-ready reports — all governed by weaveIntel’s policy engine with full audit trails.
Automatically classifies variants by pathogenicity using ACMG guidelines with explainable AI rationale.
Generates clinician-ready PDF reports with governance stamps, audit hashes, and regulatory compliance metadata.
Natural language queries over genomic datasets with citation tracking and reproducibility guarantees.
The Problem
Teams ship AI fast but lose control even faster. The result: runaway costs, data leaks, non-deterministic failures, and integration fragility.
Without token-level tracking, AI spend spirals. Teams discover $50K bills months after deployment with no way to attribute costs to features or users.
Sensitive data flows through prompts unchecked. PII, credentials, and proprietary information reach third-party APIs without detection or redaction.
AI systems fail silently and unpredictably. Without structured outputs and contract testing, the same prompt returns different results across deployments.
Every model provider has a different API. Switching from OpenAI to Anthropic means rewriting orchestration logic across your entire codebase.
How It Works
Think of weaveIntel as a loom. You bring the threads — models, tools, data. We weave them into governed, observable AI fabric.
Three Steps
Define your AI workflow as a Loom — a declarative pipeline of skills, models, and tools. Connect any provider through unified adapters.
Attach policy gates for PII filtering, content safety, cost limits, and role-based access. Every token is audited and traced automatically.
Monitor performance, costs, and quality in real-time. Smart caching reduces redundant calls. Auto-scaling handles traffic spikes.
Results
Every prompt, response, and decision is logged with cryptographic audit hashes for compliance and debugging.
Smart model routing, semantic caching, and token optimisation cut costs without sacrificing quality.
Pre-built skills, adapters, and governance policies mean you focus on your application, not infrastructure.
Automatic provider failover, circuit breakers, and health checks keep your AI systems running.
Use Cases
weaveIntel powers AI across industries and personal workflows alike.
Screen candidates, generate job descriptions, and automate onboarding — with bias detection built in.
Automate report generation, detect anomalies, and ensure regulatory compliance with audit trails.
Intelligent incident triage, automated runbooks, and predictive monitoring with full governance.
Multi-channel AI assistants with personality consistency, escalation policies, and satisfaction tracking.
Threat detection, automated response, and security analysis with PII redaction and access controls.
Budget tracking, expense categorisation, and investment insights with privacy-first data handling.
Smart email triage, auto-drafting, and follow-up tracking — your inbox on autopilot.
Appointment scheduling, document management, and task automation for busy households.
Meal planning, fitness tracking, and health monitoring with full data privacy controls.
Market
Global AI governance market by 2030, growing at 36% CAGR as enterprises demand control.
Of enterprises cite lack of AI governance as the top barrier to production deployment.
Average return on investment for organisations implementing structured AI governance frameworks.
Sources: Gartner AI Governance Report 2024, McKinsey State of AI 2024, Forrester TEI Study 2024
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