LiveGnosari
The conversational data collection platform
- Built for
- Built for Any team that collects information from people: sales, operations, HR, support, intake and claims
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Portfolio
Two pillars.
One operating model.
Neomanex builds AI that turns conversations into structured business outcomes — and develops the operational methodology that makes it repeatable.
Pillar 1 · Conversational AI
AI that turns conversations into structured business outcomes.
Pillar 2 · AI Operations
The operational methodology that makes conversational AI repeatable.
Foundation
Shared infrastructure that every product in the portfolio builds on.
Live NeoReader
Web-to-markdown API with website discovery built in
<500ms
Static page to clean markdown
- Built for
- Built for AI engineers and data teams building RAG pipelines or LLM ingestion flows
web-to-markdownwebsite discoveryingestionInternal NeoAnalytics
Privacy-first analytics for AI-powered applications
- Built for
- Built for Frontend engineers and platform teams building Nuxt applications that need accurate, privacy-respecting analytics
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Applied Research
Research that sharpens every product.
The Neomanex Lab benchmarks the exact capabilities our products rely on — model selection for Gnosari, workflow patterns for ConvOps, retrieval quality for NeoReader. Every publication feeds directly back into the portfolio.
Libraries & shared foundations
The reusable building blocks — knowledge, queues, analytics, starters — that every product in the portfolio shares.
- python
GnosisLLM
Knowledge library: loading, indexing and hybrid search over OpenSearch. Gives Gnosari and ConvOps their knowledge and search.
- python
NeoRouter
Routing, memory and semantic search engine. Powers the ConvOps brain: memories, routes and recall.
- python
NeoQueue
Redis-backed async job processing library used by every AI worker in the portfolio.
- python Full page
NeoAnalytics
Analytics aggregation layer — collects, normalises, and exposes product usage signals.