We think with AI and create new experiences through creativity. From personal reflection with OpenAlarm to portfolio-based research with OpenStockAI, explore how our ideas become products.
01 / Available now
OpenAlarm
Your patterns. Your feelings. A reply that connects.
OpenAlarm considers recurring patterns and emotional context in your diary to shape a personal AI reply. Explore suggestions based on alarm use, revisit past entries and trace place-linked plans on a footprint map.
Records are handled within the user's account scope. Diary input is separated from instructions, and replies containing secrets or internal information are rejected before storage with a security alert.
OpenStockAI puts a question in portfolio context, routes it through the appropriate research path, and organizes the response around evidence, dates and risk. It is research support, not a return promise.
Research agents work alongside a security team. Checks identify exfiltration and privilege-bypass signals, connect request blocking to redacted audit records, and support review.
AI that divides the work.
Boundaries that stay in place.
Orchestrators connect tools and agents, while product-specific safeguards check access, inputs and outputs. Explore where detection, blocking and limits on sensitive-data transmission take place.
Research agents work alongside a security team. Checks identify exfiltration and privilege-bypass signals, connect request blocking to redacted audit records, and support review.
Architecture walkthrough · not live security telemetry
OpenStockAI / 01
Input
Question · portfolio context
Selected work
01Research tools
02Specialist agents
03Synthesis & review
Security checks at request time
AI input protection and training policy
Google API user data is blocked from designated external-model inputs. Supported paths disable response storage, while security analysis and records redact sensitive information.
Read the protection scope
The security team combines server rules and optional AI-assisted review. Detected signals and operating settings determine logging, request blocking and temporary blocks.
A harness applies safeguards around AI execution. Transmission controls, redaction and output checks reduce exposure of sensitive information; provider retention and training policies are managed separately.
Inside the work / 03
Behind every result, a process.
Choose a product and follow its process. See what each stage receives, what it does and what it produces.
OpenAlarm / Alarm patterns
From everyday patterns to a considered suggestion.
Alarm records and plans inform specialist analysis, followed by checks on each suggestion.
Workflow walkthrough · On narrow screens, scroll horizontally to explore.
Workflow walkthrough / 01 — 04
OpenAlarm
Gather records
Input
Alarm events · plans
Work
Organize usage statistics and previous suggestions.
Output
Context for analysis
OpenAlarm
Sleep & waking
Input
Ringing · snoozing · dismissal
Work
Examine recurring patterns in alarm use.
Output
Pattern-informed proposals
OpenAlarm
Plans & travel
Input
Tasks · plans · location settings
Work
Consider reminders in the context of plans and travel.
Output
Plan-related proposals
OpenAlarm
Automation
Input
Alarm settings · context
Work
Consider changes that may suit automation.
Output
Automation proposals
OpenAlarm
Check proposals
Input
Specialist proposals
Work
Check evidence, conflicts and previous rejections. Failed proposals need correction.
Output
Checked proposals
OpenAlarm
Await review
Input
Proposals needing review
Work
Save suggestions for the user to inspect and act on.
Output
A choice for the user
OpenAlarm
Eligible changes
Input
Eligible automatic proposals
Work
Apply only eligible changes. Failed applications remain pending.
Output
Application result and record
Connected stages
Only relevant analysis runs. Automatic application depends on operating settings and the kind of suggestion.
In the works
OpenDataLabs
Connect verified documents and handwriting to shipping, delivery and payment schedules. Track deadlines and completion with source evidence and human review. In development.
A Privacy Harness checks task-specific allowlists before information reaches an external model. It limits unnecessary source and identifying data and blocks policy-violating requests.