AICESP is a dual AI-native platform: our production line turns a conversation about the client's business and strategy into a complete, tested, deployable enterprise system — the requirements spec, architecture, code and documents are all AI-produced and quality-gated. And every system we deliver has AI agents built in, driving the customer's business processes from day one.
"AI that generates enterprise software" is the face it monetizes today. Underneath is a domain-general, self-governing, self-evolving intelligent system — one that can understand, design, build and keep evolving long-horizon complex projects in any field. Enterprise software is its first, and best-verified, instance.
A four-stage line — req→design→develop→optimize — delivers a whole running system autonomously, end to end. Software ships a free referee (compiler, tests); that's why we lit it first — fastest feedback, fastest self-evolution.
The same engine instantiated on "operating AICESP": strategy, process, iteration and daily operations run by AI, humans handling creativity and exceptions. The self-evolution duty line, partner outreach and material generation already run here.
Strategy, science, operations, complex-system design — where an expert team takes months and there is no compiler. The barrier to a new field isn't the engine; it's "who is the referee."
Here is the moat: other fields have no free compiler. The system's truly distinctive core ability is manufacturing verification where no referee exists (adversarial multi-model checks, deterministic gates, simulation, decaying human-in-the-loop). So "opening a new field" isn't a gate to clear first — it is the reason this engine exists. The TAM isn't capped at software outsourcing; it's "autonomous long-horizon projects in any field." To be honest about maturity: instance #1 is well-verified, self-governance is running, self-evolution is still early — we're not selling "already fully autonomous," we're selling a positive slope.
Everything below is live on the public site today — real systems built by the production line, running real code with demo data. No slideware.
Government, Enterprise, Retail, Logistics live online; Manufacturing (our industry flagship) ships today. Every one passed a three-gate quality process with runtime-verified auth on every protected endpoint.
Business conversation → delivered system: 30 min requirements + 48 min design + 3 h code. For a listed-company LTC platform, after gathering business needs with the client, requirements/design/development ran from 20:02 and the system shipped 03:57 — overnight, 510 files, 43 pages, all acceptance passed.
Government edition: 43/43 acceptance, 149 secured endpoints, zero auth bypass. Enterprise edition v2.0: 26 business scenarios, 31/31 acceptance, 51 frontend pages, 100% design-coverage.
The production line that builds customer systems is itself under permanent test. Run them yourself in due diligence — we'll hand you the terminal.
✓ Model-agnostic — verified across DeepSeek, Kimi, GLM ✓ On-premise deployable, data never leaves the customer ✓ Free base editions download-gated → qualified leads ✓ Deployment service at >99% gross margin
Speed can be copied. Acceleration is hard. Jerk is nearly impossible. These four numbers are re-measured every week, fully auditable from our git history and production-line certificates. Week 28 (Jul 7–8, in progress) actuals:
Methodology: L0 product family → L1 platform → L2 self-evolution layer → L3 agent capability system → L4 human (ideas & exceptions only). The higher the layer, the harder to copy.
First-generation China SaaS died on human service costs — more customers, more losses. Our marginal delivery cost is compute. More customers → thicker constraint library → lower cost per system.
DingTalk / WeCom / Feishu sell generic collaboration tools. We deliver each customer's own business system — AI-native, private-deployable, compliance-ready. Their cost structure cannot generate a bespoke system per customer. Ours is built for exactly that.
Hard gates, generation constraints, generability design and honest BLOCKED certificates guarantee output quality regardless of which LLM does the work — verified across three model vendors with negligible variance. This is our leverage in model-vendor negotiations, and the answer to "can AI code be trusted?"
Marketing site, investor materials, mail & web sales assistants, trademark filings, this very page — produced and operated by AI with one human providing direction and exceptions. We are our own first customer, in production, today.
Single tranche, clean terms, no tricks.
≈9.1% offered. Post-money ¥66M.
We fight a three-month war with eighteen months of provisions — aggressive speed, conservative safety margin.
| T+1 month | Platform GA · free base editions open · first paying customer |
|---|---|
| T+2 months | Five editions on sale · reseller network operating |
| T+3 months | All eight industry solutions live · Series A kickoff (target ¥30–50M, priced on audited operating data) |
Use of funds: compute & model capacity, platform hardening, go-to-market. Every later round is priced on operating data, not narrative.
Watch the production line regenerate a full system live. Run the 1,100+ platform tests yourself. Click through every delivered system online. Then let's talk price.
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