Graph Attraction OS
Stop pushing messages. Start creating gravitational pull.
Graph Attraction OS turns digital signals into symbiotic relationships - building trust through value before the ask. For B2B teams, achieve $100M+ gravity pipeline with 0 SPAM complaints.
Proven Results
No vanity numbers, just infrastructure-driven growth through gravitational pull.
System Architecture
Like Palantir's ontology for data fusion, Stripe's modular APIs, and Snowflake's AI Data Cloud - built infrastructure-first with ruthless tradeoffs for ethical depth.
Production systems optimize for structure, not proximity. Graph RAG understands relationships - not just semantic similarity.

Every step orchestrated - from signal detection through strategy, campaign setup, lead capture, and performance tracking.

Enterprise-grade infrastructure designed for scale, security, and intelligent automation.

The complete orchestration flow shows how n8n coordinates every step - from signal ingestion through graph construction, play selection, human approval gates, multi-channel execution, and feedback loops.

Multi-step agentic workflow for creating hyper-personalized video content. LLMs generate concepts, parsers extract structure, Veo3 API produces videos, and automated distribution reaches multiple social platforms.

Advanced analytics pipeline using K-means clustering to segment customer feedback into actionable insights. Reviews are fetched, algorithmically clustered into themes, analyzed by LLM agents, and exported for team collaboration.

The Model
The difference between targeting accounts and shaping intent.
Modern B2B leaders don't debate outbound anymore.
They debate how intelligence should move through markets.
Aonxi introduces a new model.
Modern ABM platforms are sophisticated.
They define ICPs precisely. Monitor intent signals. Coordinate multi-channel touches. Personalize messaging at scale.
They are far better than outbound.
But they still operate on one assumption:
If we target the right accounts hard enough, engagement will follow.
ABM identifies who to contact. It optimizes how to reach them.
It does not change why they engage.
Aonxi starts one layer deeper.
Instead of optimizing touchpoints, it models decision gravity.
It asks:
Then it acts only when gravity exists.
Aonxi does not "run campaigns."
It releases insight into the system and lets engagement emerge naturally.
| Dimension | Best-in-Class ABM | Aonxi Gravitational Pull |
|---|---|---|
| Primary Unit | Target account | Decision state |
| Trigger Logic | Intent signals + rules | Live graph state (people, events, context) |
| Personalization | Message-level | Insight-level |
| Primary Action | Outreach sequences | Value release (research, POVs, peer context) |
| Engagement Driver | Relevance | Recognition |
| Buyer Psychology | "They're contacting me" | "This is about me" |
| Meeting Dynamic | Qualified, but guarded | Open, informed, self-motivated |
| System Behavior | Push optimized by data | Pull governed by proof |
| Failure Mode | Over-contact, fatigue | Inaction until conditions are right |
Because buyers don't respond to messaging anymore.
They respond to clarity.
When someone sees their situation reflected accurately - without being pitched - curiosity replaces resistance.
That's not marketing. That's physics.
ABM decides who to target.
Aonxi decides when engagement becomes inevitable.
Everything else is noise.
Book a DemoLive Demo
Watch the graph build a real relationship - from first signal to closed deal.
System finds NovaTech: $8M funding + 3 data engineering hires
Proof & Performance
Infrastructure-driven growth, measured and auditable. 100+ companies on the waitlist.
vs 33% industry
vs 16.6% industry
peer-validated
vs traditional
vs 12% cold
vs 45 days
pull vectors
low-entropy culled
weekly lift
Client X (Series A fintech startup) saw 120 ICP engagements from one whitepaper launch, yielding $500K gravity pipeline - all from graph-predicted "compliance pain" edges. The system detected funding signals, mapped the CTO's network, identified peer influences, and generated a study comparing competitor approaches to their specific regulatory challenges.
Key insight: The graph predicted 92% engagement likelihood on compliance content based on LinkedIn comment patterns and hiring signals for a Head of Risk & Compliance role.
All metrics tracked in append-only proof ledger. Full lineage from signal to outcome.
Book a DemoTestimonials
Real results from teams who stopped pushing and started attracting.
"We went from cold outreach that got ignored to warm conversations that closed. Our gravity pipeline jumped from $2M to $12M in one quarter. The system found angles we never would have thought of - like connecting our product to a regulatory change that was hitting our prospects hard."
"The peer benchmark studies were a game-changer. CTOs actually responded because we were giving them research they needed, not pitching them. One study led to 40 qualified meetings in a month. We've never seen anything like it."
"What sold me was the human approval gate. Every message goes through our team before it sends. Zero spam complaints in 8 months. Our legal team actually likes this tool - that's a first for anything in marketing."
"The relationship mapping is incredible. It found a connection between our CEO and a prospect's board member we didn't know existed. That warm intro turned into our largest deal this year. You can't buy that kind of intelligence."
