Seven Technology Pillars (2026)
Native multimodal foundation, multi-agent collaboration and decoupled knowledge/inference — the 2026 enterprise-AI base. Tap any card for the dedicated technology page.
Tap into each technology
Each pillar has its own page with long-form description, key capabilities, scenarios and quantified outcomes.
Native Multimodal Unified Foundation
Hybrid autoregressive + diffusion architecture — AR text tokens with multi-step image-token denoising. Native full-modal understanding, generation and reasoning across text, code, audio, image and video as the cross-modal base for world models.
Multi-Agent Collaboration
A perceive → plan → execute → reflect cognitive loop with task decomposition, tool calling, experience accumulation and continuous iteration — wired for finance research/risk/compliance and manufacturing production/QC/R&D.
Decoupled Knowledge & Low-Cost Inference
DeepSeek-based architecture decouples knowledge storage from inference compute — a lighter backbone with sharply lower latency and cost. Enterprise knowledge is embedded inline, replacing bolt-on RAG with more consistent, expert outputs.
Skills Modular Capability System
Industry-standard workflows packaged as reusable instruction sets — lower token cost, eased context bottlenecks and steadier execution. Non-technical teams ship fast; MCP-compatible and complementary to deep reasoning.
Local-First Agent Gateway (OpenClaw)
End-to-end local data processing — data stays in domain, compliance-controlled, deployable on PC, server or edge. Multi-channel ingress and persistent semantic memory eliminate agent context overflow and execution drift.
Multimodal Data Fusion & Vector Data Lake
Unifies structured (ops, finance, customer) and unstructured (voice, video, documents) data with standardized OCR/ASR/CV pipelines. A vector data lake with multi-tenant isolation and intelligent hot/cold tiering.
Privacy Computing & Compliance Security
Federated learning and GNN-based cross-institution modeling keep data in domain. Compatible with domestic chips (Ascend, Cambricon) and OS (Kylin, UOS), with hybrid deployment and full observability.
Defined scope. Accountable delivery.
Staged pricing & acceptance
Discovery, pilot and rollout have separate scope and fees. Contracts define baselines, evaluation samples, acceptance metrics and responsibility. Results are not unconditionally guaranteed.
Customer business data stays off-chain
Business records and personal data are not written to a blockchain. Confirm deployment region, model providers, access, retention and deletion in writing before work begins.
Clear contracting & delivery responsibility
Before signing, obtain and verify the legal entity, registration, jurisdiction, delivery owner and dispute terms. DAO collaboration does not replace contractual responsibility.