4-stage delivery
These scenarios have all been deployed at customer sites — but every factory's process, customer conventions and standards differ, so customization is non-negotiable. That's exactly what we do.
P0 · Pain-point diagnosis
1-2 weeks free on-site / remote AI opportunity mapping; deliverable: backlog + priority recommendations
P1 · PoC validation
2-4 weeks end-to-end PoC on the highest-ROI scenario, validated on real customer samples
P2 · Custom delivery
End-to-end implementation + go-live, integration with ERP / MES / CAD, training and full documentation
P3 · Continuous hosting
Post-launch we run it: platform + model + rule library + SLA. No customer AI team required.
6 differentiated capabilities
S1 · Platform base + industry Skill customization
combo agent platform + 50+ reusable Skills, no rebuilding from scratch.
- Generic base covers Agent / Session / Memory / Hook / Channel
- 50+ official Skills across docs, review, office, requirements, etc.
- Customer scenarios = composition + bespoke Skills
- 60%+ shorter implementation vs. greenfield builds
Reuse the base, customize only what's unique to the customer.
S2 · Domain expertise → Skill packaging
Senior know-how, customer conventions and error patterns crystallized as reusable assets.
- Customer conventions auto-injected into new projects
- Error patterns drive monthly rule library evolution
- Exemption rationales fully audit-trailed
- Dramatically shorter new-hire ramp-up
Knowledge as an asset is the real manufacturing-AI moat.
S3 · Explainable + Sign-off-ready
Every AI output ships with evidence + reference; engineers retain final authority.
- Every field includes source + confidence
- Critical calls attach evidence screenshot + rule ID
- AI never replaces engineer sign-off
- Audit trail for both internal review and external pushback
Black-box AI is a non-starter in manufacturing.
S4 · Deep enterprise system integration
Lark / WeCom / DOORS / Polarion / Jira / MinIO — already deployed.
- Collaboration: Lark / WeCom / DingTalk
- Requirements: DOORS / Polarion / Jama / Lark Project
- Code: Gerrit / GitLab / GitHub
- Storage & docs: MinIO / standard document formats
AI drops into existing systems — no greenfield required.
S5 · On-prem + physical isolation
Data never leaves your enterprise, never enters any cross-customer pool.
- On-prem / intranet / SM-crypto compliance supported
- Per-customer physical tenant isolation
- No industry benchmarks, no cross-customer data flow
- Compliant with PIPL / GDPR
Strict data sovereignty.
S6 · Continuous hosting & ops (NEW)
We build → we maintain. No customer AI team needed.
- Platform ops: servers / models / storage
- Seamless migration to new models
- Rule library evolves with the business; false-positive monitoring
- 7x24 SLA support
An AI team easily costs $1M+/yr. We do it for you.
Anyone can demo a generic AI Agent. Running one inside your factory's daily production loop and maintaining it long-term — that's what we specialize in.
Track record so far
Industries deployed
2+
Engineering contracting + automotive R&D; more in PoC
Reusable Skills
50+
Composable base, no rebuilding from scratch
Customer hosting model
Live
We run post-launch ops; no customer AI team required
How we price projects
No fixed price tags. A full customization project is priced in these 4 parts. Each part requires sign-off before the next; cancellable at any point.
1-2 weeks · Free
2-4 weeks · Per-week pricing
Per-project pricing
Annual subscription
The next factory to make AI real could be yours
1-2 week free pain-point diagnosis. No commitment, no charge.
Customers in production
Overseas window-engineering contractor · multiple top OEMs / Tier1 (NDA)
Customer scenarios & feedback
After dropping generic AI into specific factory workflows — what customers actually said
We doubted AI would work in a factory our size. Now we use it every day.
Schedule says 1500, elevation drawn 1480 — the machine flags it in a second with the screenshot. I just sign the red items.
Drawing reviewer
Window engineering
Customer uploads drawings, the issue list is right there. What I forward back is plain English, no more manual translation.
Sales rep
Outbound contracting
The recommended price ties back to factory floor + historical neighbors + multipliers. Margin approvals are auditable; finance stopped chasing me.
Sales director
Engineering contractor
Customer conventions live in the system, no more re-briefing every new hire. Independent ramp-up dropped from six months to one or two.
Project manager
Mid-size manufacturer
We don't have an AI team. They built it AND maintain it. For a small shop that's everything.
GM
Small factory
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