Four Core Service Capabilities · Disrupting MBB Consulting
From leverage-point diagnosis to agent process factory, from DAO expert collaboration to global distributed delivery — no slides, only running AI systems.
AI Ready Leverage Diagnosis
AI scans workflows, cost structure and time-spend to identify the highest-leverage profit drivers, then outputs a leverage report, deployment roadmap, timeline and cost model — replacing months of legacy discovery.
- AI auto-scan of workflows & cost
- Pinpoints profit leverage points
- Actionable roadmap output
AI Agent Process Factory
Auto-builds industry AI systems and agentic workflows, generating runnable code, processes and integrations: clinical discharge automation, finance reports, end-to-end retail AI, manufacturing QC and predictive maintenance.
- Auto-generated production systems
- Industry agentic workflow library
- No slides — only deployments
Global AI DAO Expert Network
Enterprises post needs on-chain; AI strategists, ML engineers, business advisors and implementation engineers (NFT-bound) bid and assemble; delivery is verified on-chain and settled by smart contracts against milestones.
- On-chain bidding & team assembly
- Delivery & acceptance attested on-chain
- Smart-contract staged pricing & acceptance
Global Distributed Delivery Network
Five regional hubs across APAC, EMEA, Americas, MEA and LATAM operate in concert: local on-site teams, global remote experts in 24/7 relay, with data residency compliant with GDPR, CCPA and local law.
- 5 distributed regional hubs
- Local on-site + 24/7 remote relay
- Data-residency compliance
Multi-Platform Adapter — Never Locked to a Single Backbone
Hyperscaler ecosystems are tightening their moats. Our cross-backbone abstraction layer hands the freedom of choice back to SMEs — switch by cost, performance and compliance.
Technical Path
Middleware and standardised interfaces compatible with all major foundation-model platforms; decouple business logic from models.
Decoupling
Integrate once; route on demand across OpenAI, Claude, Gemini and compliant domestic backbones.
Flexible Switching
Auto-switch backbones by price, latency, compliance and data-residency — DAO runs the complex integration and ops.
Residency & Compliance
Meets GDPR / PIPL / CCPA across jurisdictions; sensitive data can stay in-region on local backbones.
Cost Control
Mix models by task difficulty and price elasticity — cut 30–60% inference cost on general tasks.
Anti-Lock-in Insurance
Hot-swap within 72 hours when any platform changes policy, pricing or availability.
AI-Automated Delivery Process
Seven Technology Pillars (2026)
Native multimodal foundation, multi-agent collaboration and decoupled knowledge/inference — each pillar has its own page, tap any card.
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.
Six Products (2026 Edition)
From the native multimodal model platform to a Multi-Agent OS, Skills library and local-first digital-employee gateway — each product has its own page, tap any card.
Enterprise Native Multimodal Model Platform
Private / on-premise deployment with full-modal I/O for finance, manufacturing, energy and retail. Built-in hallucination suppression — LLM + classical algorithms + rule engine, validated end-to-end by RAG and knowledge graphs.
Multi-Agent Operating System
From single agent to multi-agent collaboration — task scheduling, sandbox isolation, memory management and model assembly. Pre-built office, finance, risk, marketing and ops agents work out of the box.
Skills Vertical Workflow Library
Packaged high-frequency workflows for financial risk, retail pricing, manufacturing process and energy inspection — one-call invocation, lower dev barrier, less wasted inference and clean integration with existing systems.
Local-First Digital Employee Gateway (OpenClaw)
Local deployment with secure, controlled data — integrates with WeCom, DingTalk and Feishu. Executes processes automatically and remembers business rules, replacing repetitive manual work.
Multimodal Data Governance & Vector Lake Platform
One-stop cleaning, labeling, vectorization and knowledge-graph construction — the fuel system for enterprise AI. Real-time multimodal ingest and feedback loops drive continuous model iteration.
AI Engineering & Ops Platform
MLOps + Agent Sandbox — model stress testing, observability and automated iteration. A microservice + agent hybrid architecture compatible with LLM, Chain and Graph execution engines.
Tian Suan AI Super Employee (Omni-Channel Short-Video Ops)
One AI super-employee replaces 10 marketing/ops staff — batch remix, multi-platform publishing, automated lead capture, DM-to-WeChat funnels, humanlike AI replies and global supervision. Covers script, capture, edit, publish and operate end-to-end with 10–50× throughput.
Four Global AI Dao Service Standards (Landing Methodology)
Scenario selection → technical framework → engineering path → compliance baseline — every delivery ships measurable business value.
Scenario Selection Standard
Must-solve pain, accessible data, quantifiable value, low deployment barrier — we only take on high-success scenarios that ship measurable ROI.
Technical Framework
Multi-Agent at the core, multimodal fusion plus domain knowledge to suppress hallucinations — explainable, traceable enterprise AI.
Engineering Path
Modular design, platform-level reuse, continuous iteration to drive cost down — every delivery becomes a reusable asset for the next.
Compliance Baseline
Local deployment, data stays in domain, domestic hardware/OS compatibility, traceable and explainable — the security & compliance baseline for critical industries.
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.