Collaborator & Partner Hub

Building the zero-exfiltration semantic layer for the autonomous agent era.

The Opportunity

Enterprise adoption of AI agents is bottlenecked by data infrastructure. 88% of enterprise AI pilots fail in production because LLMs are fed bloated, raw JSON context dumps—creating unsustainable token costs, high latency, and severe privacy risks.

Dataspore OS replaces context dumps with pre-computed, deterministic data contracts, keeping sensitive PII strictly within the customer's perimeter.

94.2%

Context Reduction

Drastically reduces LLM token overhead by serving clean metric contracts.

<10ms

Query Latency

Raw PII Exposure

Local semantic transformation ensures zero exfiltration of sensitive data.

Core Architecture

[ Ingestion Gate ] ---> [ Semantic Transformer ] ---> [ Analytics Cache ] HubSpot / Stripe / GA4 Identity Unification ClickHouse Engine (<10ms) Zero-Exfiltration Perimeter Model Context Protocol (MCP)

Identity Hub (The "Who"): Unifies disjointed touchpoints under a canonical Dataspore_ID.
Event Ledger (The "What"): High-speed, immutable event store for complete agent auditability.
Metric Layer (The "Truth"): Pre-computed, machine-readable analytical views for downstream LLM agents.

Who We Are Looking For

We are actively engaging with engineers, associates, and design partners who want to build foundational AI infrastructure:

Technical Co-Founders & Core Engineers: Hands-on experience with ClickHouse, event-driven pipelines, Python/Rust, or LLM agent frameworks (Model Context Protocol, LangChain/LlamaIndex).
Design Partners & Strategic Associates: Data leaders looking to cut enterprise AI costs, enforce data privacy, and run production-grade autonomous workflows.

Ready to Collaborate?

Review the architecture, test the environment, or discuss joining the team.

james@dataspore.net
Connect with James Atwood (Founder)