Nexus is the modular, cloud-native foundation behind every Veloxs product — seven independently deployable layers that turn fragmented data, conversations, and workflows into secure, context-aware intelligence. The same foundation we use to build our own products, available as a starting point for teams who want to ship governed AI without rebuilding the plumbing.
Every AI prototype reinvents the same infrastructure from scratch — ingestion, retrieval, guardrails, audit logging, and security controls. Nexus packages all of it so your team focuses on the intelligence, not the plumbing.
spent rebuilding ingestion pipelines, retrieval layers, guardrails, and audit logging for every new use case.
ever reach production — the non-model engineering is harder than the model, and most teams underestimate it.
Nexus is the same foundation Veloxs uses to build Contexion and every product in our portfolio — battle-hardened from day one.
Each capability is independently composable, model-agnostic, and production-ready. Integration happens through data contracts (JSONL), config references, CLI subprocess contracts, and HTTP — never through Python imports. Any layer can be swapped for a production adapter without touching the others.
Unify data from SaaS apps, databases, file stores, and event streams into a governed, AI-ready foundation with full lineage — REST APIs, batch drops, Kafka streams, and Debezium CDC.
ETL/ELT pipelines, document chunking, and metadata extraction — turning raw signals into context-rich, semantically chunked intelligence at scale.
Vector search, knowledge graphs, hybrid retrieval, and ranking — grounded, context-aware answers anchored in your real data, with deterministic local embeddings for reproducible dev.
The control plane every prompt flows through — Unicode normalization, PII detection, prompt-injection defense, policy enforcement, and grounded RAG with confidence scoring, in sequence.
The single front door for users, apps, and AI agents — API-key auth, identity binding, channel capability checks, and a normalized response via REST, SDK, or CLI.
Fernet AEAD encryption, HKDF-SHA256 key derivation, RBAC, tenant isolation, TLS validation, and JSONL audit logging — consulted by all six other layers.
Metrics, structured logs, distributed traces, and AI interaction events — written as JSONL locally, with declarative exporter config for every major observability platform.
eval / exec / pickle / os.system anywhere. Fail-closed security defaults. Subprocess hardening on every CLI path. This is what makes Nexus production-safe — not an afterthought, the architecture itself.
Integration recipes for the most common enterprise AI patterns — so your team focuses on the differentiating logic, not the scaffolding.
Production retrieval-augmented generation with chunking, ranking, citation controls, and confidence scoring on every answer.
Tool calling, memory, guardrails, and human-in-the-loop checkpoints — production-grade orchestration for autonomous workflows.
Pre-built connectors for SaaS apps, databases, file stores, and event streams — with governed lineage from source to answer.
Tracing, evals, drift detection, and feedback loops — measure and improve AI behavior in production, continuously.
AI-driven workflow automation, governed analytics, and intelligent decision support for organizations modernizing operations.
Conversational commerce, hyper-personalization, and lifecycle automation — from first interest to loyalty.
Every Nexus layer ships a deterministic local implementation suitable for dev and CI, plus a documented extension contract for production. Wire in your own LLM, vector DB, KMS, SIEM, or policy engine — without touching any other layer.
| Extension point | Layer | Ships today | Production swap |
|---|---|---|---|
| Embedding provider | Retrieval | Deterministic local hash | OpenAI · Bedrock · sentence-transformers |
| Vector DB | Retrieval | File-backed JSON | pgvector · Pinecone · Weaviate · Qdrant · OpenSearch |
| Graph DB | Retrieval | File-backed JSON | Neo4j · AWS Neptune |
| Model gateway | Guardrails | Answer composition only | OpenAI · Anthropic · Bedrock · Azure · Vertex |
| PII engine | Guardrails | Regex + Luhn validation | Microsoft Presidio · AWS Comprehend |
| Policy engine | Guardrails | Substring policies | OPA · Cedar · custom DSL |
| Auth provider | Engagement | API keys (constant-time) | OIDC · JWT · SSO |
| Session store | Engagement | In-memory dict | Redis · PostgreSQL |
| Key material | Security | Env var → HKDF | AWS KMS · HashiCorp Vault · Azure Key Vault |
| Audit storage | Security | JSONL append | SIEM · data lake · WORM storage |
| Telemetry export | Observability | Config validated (no push) | OTLP · Prometheus · Datadog · Splunk · CloudWatch |
| Object store | Pipeline | Local filesystem | Amazon S3 · Azure Blob · MinIO |
Every external dependency is behind a documented extension contract. Choose the integration pattern that fits your team's architecture today — and change it later without a rewrite.
Import NexusPlatform directly. Simplest call path — swap the mock for a real guardrails gateway when ready.
Wire your own policy engine via the Authorizer Protocol — bring your existing access-control logic.
Start the engagement layer as a FastAPI service. Front with your ingress and terminate TLS there.
The root nexus CLI invokes each layer via subprocess — never imports child-layer code directly.
Deploy each layer as its own container. Cross-layer integration via config, JSONL, and HTTP — no shared runtime.
AEAD encryption, Luhn-validated PII detection, SSRF defense, prompt-injection normalization, constant-time auth, and fail-closed key handling are the baseline. This is rare in AI frameworks, and it's the first thing security teams check.
Every layer ships its own pytest suite. No random seeds, no network calls, no cloud credentials, no model downloads — green build on every commit, safe for any CI gate.
Adopt Nexus today, and the rest of the portfolio is already wired in for tomorrow — the same governed, context-aware intelligence layer powers every product we ship.
Turn every connection into context. Branded digital business cards, intelligent lead capture, and AI-powered relationship intelligence for individuals, teams, and enterprises.
Take a tour →Your context-aware chief-of-staff — capturing context, automating follow-ups, and keeping you continuously informed across every channel.
Get early access →Conversational commerce for local brands — conversational ordering, personalized recommendations, and automated delivery coordination.
Join the waitlist →From a single-process library to a full per-layer microservice deployment — we'll help you choose the right starting point and grow from there.
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