The only orchestration framework where every agent action is anchored to a real location, a real satellite observation, and a cryptographic proof.
Today's orchestration frameworks are built for digital space. They call APIs, process text, generate outputs — but have no concept of where an agent physically is, what it physically observed, or how to prove any claim about the real world. GEIANT fills that gap.
LLM agents that call APIs, process text, generate outputs. No spatial context. No physical-world anchoring. No way to prove a claim about the real world.
Every agent action is anchored to an H3 cell, a signed satellite observation, and a cryptographic proof chain. Jurisdiction-aware. Verifiable. Auditable.
Every GEIANT agent action follows the same verifiable pipeline. The full chain is stored in Spatial Memory — cryptographically signed, queryable, auditable.
Agent receives an H3 cell index at resolution 5–8. This defines its operational territory. Delegation chains enforce jurisdiction.
GEIANT queries Microsoft Planetary Computer for the latest Sentinel-2C tile over the cell. Filters for cloud cover, acquisition date, band availability.
Prithvi-EO-2.0 classifies the tile — flood detection, land cover, anomaly scoring. Clay embeddings encode semantic meaning. WxC adds weather context.
The full perception chain — tile ID, model ID, cell, timestamp, confidence, class counts — is written to PostGIS with version history.
The agent signs the perception result with its Ed25519 key. This is the proof of observation — cryptographically tied to the agent's GNS identity.
Real deployments. Real infrastructure. Real deadlines.
A major grid operator deploys GEIANT agents across millions of smart meters. Every anomaly alert is backed by a satellite flood/event classification and weather context — no false positives without physical proof.
Autonomous agents track vehicles across regulatory boundaries. Proof-of-Trajectory from the GNS Protocol confirms physical presence at each waypoint — GPS spoofing is cryptographically detectable.
After a flood event, GEIANT agents query pre- and post-event Sentinel-2 tiles, run Prithvi classification, cross-reference WxC precipitation data, and produce a verified impact map with full provenance.
National-scale FTTH rollouts span hundreds of thousands of street cabinets, millions of premises, and hard regulatory deadlines. GEIANT gives every installation crew, every cabinet, and every activated line a verifiable H3-anchored identity — turning a logistics problem into a provable audit trail.
GEIANT is running in production, processing real satellite data over real territory.
GEIANT follows the proven open-core model: a self-hostable open core under Apache 2.0, and a managed platform that handles infrastructure, scaling, and compliance for teams that need it.
GEIANT is the full physical-world deployment. GNS-AIP is the identity and delegation layer — standalone, open source, and framework-agnostic. Drop it into any LangChain, CrewAI, or OpenAI Agents deployment in under 5 lines.
Every AI agent that runs code, queries data, or takes action needs to answer three questions a regulator will eventually ask: Who authorized this agent? What scope was it given? Can you prove it?
GNS-AIP answers all three with Ed25519 cryptographic identity, signed delegation chains, and a virtual breadcrumb trail — without recording prompts or outputs. The identity primitive is identical to GEIANT's, which means an agent proven in the field can be trusted in the cloud.
→ Full developer docs at gns-aip.gcrumbs.com// npm install @gns-aip/sdk import { generateAgentIdentity, createDelegationCert, computeComplianceScore } from '@gns-aip/sdk'; // 1. Agent gets a permanent Ed25519 identity const agent = generateAgentIdentity(); // 2. Human principal delegates scope — cryptographically signed const cert = createDelegationCert({ from: humanKeypair, to: agent.publicKey, scope: ['read', 'write'], territory: ['8428309ffffffff'], // H3 cell — EU jurisdiction ttl: 86400 }); // 3. Check compliance tier at any time const score = computeComplianceScore(agent); // → { tier: 'VERIFIED', score: 62, dimensions: { delegation: 25, territory: 18 } }
# pip install gns-aip from gns_aip import AgentIdentity, DelegationCert, ComplianceScorer # 1. Create agent with Ed25519 keypair agent = AgentIdentity.generate() # 2. Delegate from human principal cert = DelegationCert.create( issuer=human_keypair, subject=agent.public_key, scope=["read", "write"], territory=["8428309ffffffff"], ttl=86400 ) # 3. Score compliance — real-time, auditable score = ComplianceScorer.compute(agent) # ComplianceScore(tier='VERIFIED', score=62)
// npm install langchain-gns-aip import { GnsAipCallbackHandler } from 'langchain-gns-aip'; import { LLMChain } from 'langchain/chains'; // One callback handler — that's it const handler = new GnsAipCallbackHandler({ agent, delegation: cert }); const chain = new LLMChain({ llm, prompt, callbacks: [handler] // Every LLM call now carries a signed identity }); // Every chain invocation is now signed, scoped, and auditable await chain.invoke({ input: "Analyse this grid anomaly" });
# pip install crewai-gns-aip from crewai_gns_aip import GnsIdentityTool, gns_step_callback from crewai import Crew, Agent, Task analyst = Agent( role="Grid Analyst", tools=[GnsIdentityTool(identity=agent, delegation=cert)] ) crew = Crew( agents=[analyst], tasks=[task], step_callback=gns_step_callback # Every step signed + logged ) crew.kickoff() # Full delegation chain in audit log
Self-host the open source stack for free. Move to GEIANT Cloud when you need managed inference, spatial memory, and enterprise SLAs.
GEIANT is in active deployment with enterprise customers. Tell us about your use case and we'll be in touch within 24 hours.
A member of our team will reach out within 24 hours.
In the meantime, check out the open-source repos and the GNS-AIP SDK.
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