Company, People, and Partnerships

Decision

Present Memova to ODMs as a Memory OS and agent-action system spanning five hardware entry points, not as a buyer seeking a quote for one commodity recorder.

Primary message:

One software system, five hardware entry points. Each device captures a different part of real-world context, while Memova turns that context into durable memory and user-confirmed action.

The five current consumer price directions are:

These are retail price directions, not target BOMs or final commitments.

Recommended Partnership Ask

Frame early support as strategic co-investment rather than asking bluntly for 1,000 free units:

• reduced or shared NRE;
• sample, tooling, or certification cost rebated against later POs;
• strategic-cost support for the first 500-1,000 units;
• milestone-based pricing, capacity, and engineering support;
• a reusable reference design that can expand to a second and third form factor.

Memova contributes product definition, Memory OS, knowledge base, agent workflows, software updates, global user testing, brand/GTM, and a multi-SKU roadmap. The ODM contributes hardware reference designs, acoustics, antennas, low power, thermal/structural/DFM, firmware interfaces, certification, pilot production, and scale manufacturing.

External-Claim Guardrails

• “World first” may be used only for Memova's specifically defined Personal Superalignment platform category framing. Do not broaden it into claims that Memova invented personal AI memory, LLM Wiki, knowledge bases, or AI alignment.
• The earlier US$1.5M financing target is historical planning language and must be refreshed against completed financing before reuse.
• Founder revenue history, team roles, and academic credentials require approved public wording.
• Medical, legal, and accessibility use cases are research/target markets, not clinical or professional efficacy claims.

Approved Team And Capital Presentation

• Present Sun Mingyu, Du Tianwei, Chen Chen, and Cheng Yang as four equally important core founding-team members with equal visual and narrative weight.
• Sun Mingyu's prior company reaching US$30M annual revenue in year three is founder track record, not Memova revenue.
• Company-confirmed completed investment/support: Silicon Valley USD fund and MiraclePlus.
• Current outreach/relationship development: Sequoia Capital and Andreessen Horowitz (a16z). These two must never be placed in the completed-investor area or described as invested.
• Capital and ecosystem content appears after the growth-plan section in the ODM artifact.

Chen Chen｜Memova 数据科学负责人岗位计划（2026-07-22）

材料定位

这是一套由 Chen Chen 本人讲述的岗位 Pitch，不是第三方人才评估。全稿使用第一人称，目标是向团队说明：我的教育与职业背景、我对 Memova 的理解、数据科学负责人职责，以及前 90 天到 12 个月的执行计划。

叙事结构

• 第 1–5 页：个人介绍。按 Stanford Civil & Environmental Engineering PhD + Computer Science Machine Learning minor、Twitter、PayPal、OpenAI（2025–至今）的时间线展开；学术页包括 3 篇 Building and Environment 期刊论文和 1 篇 IBPSA Building Simulation 2021 会议论文；职业页强调实验、因果推断、预测和产品决策能力。
• 第 6–7 页：Memova 公司定位与我的岗位使命。Memova 将个人 Context 转化为可理解、可对齐、可执行的行动；数据科学负责人负责建立从 Context 到可靠行动的数据闭环。
• 第 8–10 页：三层高级数据科学框架——Personal Context Intelligence、Alignment & Workflow Policy、Learning, Evaluation & Governance。
• 第 11–15 页：经验到岗位计划的映射、0–30 / 31–60 / 61–90 天交付，以及 6–12 个月平台化路线图。
• 第 16 页：以第一人称提出需要团队共同确认的四个决策。

关键决策

• 删除 Meta 与 Instagram 的所有经历、指标和相关论据。
• 技术计划从五个分散模块压缩为三张高层框架页，强调可理解性、决策策略与可信闭环。
• 90 天优先完成一个真实场景的端到端闭环；随后再平台化数据、模型、实验与治理能力。
• 自动化坚持人类主导：建议、起草与高影响执行设置不同门槛，并保留确认、撤销、审计和回退机制。

最终产物

• outputs/chen-chen-memova-head-of-data-science-plan-2026-07-22.pptx
• 16 页，中文为主，机构 Logo 辅助；视觉语言参考用户提供的 PPT参考(1).pdf。
• 已完成逐页视觉检查、画布越界检查和文件完整性验证。