About Daylogue

How Daylogue Uses AI

A plain language explanation of what the AI does, what it does not do, and how your data is handled.

A warm everyday moment of private reflection

Daylogue uses AI in several parts of the product. This page explains exactly what the AI does, what it does not do, what data it sees, and how that data is handled at each step. No jargon, no vague reassurances. Just how it actually works.

Using Daylogue without AI

No AI mode stops newly submitted content from being sent to Daylogue's AI and voice services on supported platforms. It is not a local-only mode: entries still sync to and are stored by Daylogue under the Privacy Policy. You can keep using manual journaling, curated prompts, structured check-ins, calendar history, and manual tags. Rules-based patterns are a separate consent choice and use structured fields plus eligible accepted manual tags; sensitive tags are left out.

Chat, guided and voice check-ins, new AI-written Stories and tailored insights, automatic tags, OCR, semantic search, and generated programs stop. Some saved AI-created Stories and generated Programs display a history label on the web; a label is not promised for every historical artifact or platform. Turning AI processing back on applies only to future content; protected history is never backfilled. No AI mode is supported on web, iPhone, and Apple Watch. Android support is not available yet, and account activation is rolling out gradually.

What the AI does

AI powers five specific features in Daylogue:

  • Follow-up questions during check-ins. When you check in, the AI reads what you wrote and generates a relevant follow-up question. This is what makes the check-in feel like a conversation instead of a form.
  • Mood, energy, and stress extraction.The AI reads your words and identifies signals about how you are feeling. If you say "I barely slept and everything felt hard today," the AI notes low energy and elevated stress without you needing to move a slider.
  • Pattern identification.Across days and weeks, the AI looks for recurring themes, correlations between metrics, and shifts in your emotional patterns. This is how Daylogue surfaces observations like "your stress tends to be higher on days when your sleep is below six hours."
  • Narrative summaries. The AI reads across multiple check-ins and synthesizes them into a narrative about your recent days. This is not a summary of one entry. It is a synthesis of patterns across time, written in a reflective and warm tone.
  • Chromascape color palettes. Based on the emotional tone of your check-in, the AI generates a unique color palette that represents the feeling of your day. This is an expressive feature, not an analytical one.

What the AI does not do

These are firm boundaries, not aspirational goals:

  • It is not designed to diagnose. Product rules prohibit condition labels and clinical determinations. AI output can still be wrong, so it should not be treated as medical guidance.
  • It is not designed to direct your care. Product rules limit output to observations and reflective questions, not treatment or medical recommendations. AI output can still make mistakes.
  • AI processing uses listed service providers. Daylogue sends the content needed for a chosen feature to the subprocessors described in the Privacy Policy. Organization administrators do not receive individual journal entries through team aggregates.
  • It receives limited product context. A request can include the current check-in and selected recent metrics or themes needed for that feature. Daylogue stores entries and product outputs as described in the Privacy Policy.
  • It is not professional care. Guardrails instruct the AI to stay within self-reflection boundaries, but generated text may be inaccurate. Daylogue is not therapy, medical care, or a crisis service.

How the processing works, step by step

Here is what happens when you complete a check-in that uses AI features:

  1. 1.Encryption in transit, and vault storage where an account has a key. Protected in transit by TLS. Where an account has an encryption key, entries saved to the vault are encrypted with AES-256-GCM. Treat that as protection against storage-layer exposure rather than as a promise about what Daylogue can read: Daylogue is not end-to-end encrypted.
  2. 2.Brief decryption for AI processing. For features that require AI (follow-up questions, pattern detection, narratives), an entry held in the vault is briefly decrypted in memory; either way, the entry is sent to the AI provider (AWS Bedrock) over an encrypted connection (TLS 1.3).
  3. 3.AI processes and returns results.The AI provider processes the request under Daylogue's configured service terms. Current retention and training commitments are described in the Privacy Policy and subprocessor list; Daylogue does not rely on a blanket claim that no provider-side operational record can exist.
  4. 4.Results are stored server-side. The AI-generated results (pattern observations, narrative text, extracted metrics) are stored unencrypted in the database, since they need to be readable server-side to power those features.

Daylogue's servers read your entries to write your narratives. Daylogue is not end-to-end encrypted. If you would rather your writing never leave your device at all, that is a reasonable preference; Daylogue does not offer that mode today. Daylogue is transparent about exactly how your data moves.

What data the AI sees

During processing, the AI receives:

  • The text of your current check-in (during processing only)
  • Your recent mood, energy, and stress history (for context when generating patterns)
  • Your themes (for relevance in follow-up questions and narrative generation)

Generative requests are designed to minimize direct identifiers. Voice-session infrastructure may use an account-scoped identifier so Daylogue can bind policy and revoke access safely. Provider handling follows the current service configuration and subprocessor disclosures.

AI training: a firm policy

Daylogue does not use your entries to train its own models. Third-party handling follows the current service configuration, written terms, and subprocessor disclosures.

AWS Bedrock is one of Daylogue's AI providers. Its handling of customer data follows Daylogue's current configuration and written terms, which are tracked in the subprocessor disclosures.

The voice processing path

Voice check-ins use a separate processing path from text check-ins. Here is how it works:

  • Audio is streamed to ElevenLabs in real time for voice interaction. Current provider retention terms are listed in the Privacy Policy and subprocessor list.
  • Transcription happens within the live session. The resulting check-in text and provider handling follow the terms described in the Privacy Policy and subprocessor list.
  • The resulting check-in text (what you said, transcribed) follows the same encryption and AI processing path as a typed check-in.

Related pages

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What is Daylogue?

Daylogue is a pattern journal — it reads your daily entries and detects the emotional patterns running through them across time. Instead of a blank page, Daylogue starts with a short daily check-in, then surfaces what your days have been trying to tell you: what keeps showing up, what shifts after certain people or places, and what gets heavier or lighter over weeks and months.

Unlike general-purpose writing apps or note-takers, Daylogue is built specifically for emotional pattern recognition. It tracks mood, energy, stress, and sleep through conversational check-ins — by text or voice — and synthesizes those signals into an evolving narrative that reads your life back to you. Entries are restricted to your account by per-user access controls in the database and protected in transit by TLS, and entry text is kept out of Daylogue's application logs and error reports. Daylogue's servers read your entries to write your narratives, and Daylogue is not end-to-end encrypted.

How Daylogue works

Daylogue's narrative engine reads across entries — it does not generate advice or prescribe action. The engine synthesizes patterns from multiple check-ins over days and weeks, producing a personal narrative that reflects what actually happened rather than what you should do about it. This is the core mechanic: reads, does not advise. Entries sync to Daylogue's servers, which read them in order to write those narratives. No streaks. No pressure. No one else using Daylogue can see your entries.

About the company

Daylogue is developed by Daylogue LLC, headquartered in Los Angeles, CA. The company was founded in 2026 and builds self-awareness tools centered on privacy-first design and emotional pattern recognition. Daylogue's flagship product is a pattern journal that reads daily entries and detects the emotional patterns running through them over time.

Daylogue is not therapy

Daylogue is a self-awareness and reflection tool, not a therapy product. It is not a replacement for professional mental health care, therapy, counseling, or clinical support. It does not assess, diagnose, or treat any mental health condition. If you are experiencing a mental health crisis, please contact a licensed professional or crisis service. Daylogue may be used alongside therapy as a tool for self-reflection and pattern awareness, but it is not therapy and should not be treated as such.

Where to learn more