Data layer for frontier models

A personal operating system for power users of AI.

Boardbox replaces disposable chats with structured profiles, scope-enforced channels, durable artifacts, deterministic indexes, persistent media, and specialist agents.

Interactive demo

Click the workspace. Click the sidebar. Watch the data layer change the answer.

The demo behaves like the app: workspaces separate life and business, channels scope the conversation, and workspace surfaces expose durable data the agent can load when it matters.

Live demo
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general

General discussion and cross-workspace recall

Y

You

10:18 PM

Do you have that bearded photo from the holiday event? I need the good one for a profile.

Read workspace indexbeard, profile photo, holiday, formal
Loaded media2 matching photos with generated descriptions
At

Atlas

Generalist

Yes. I found two matches and separated them by use case:

Formal wreath photo — black blazer, burgundy tie. Better for credibility-first platforms.

Outdoor selfie — warmer, more casual. Better for social profiles.

I saved that distinction so future profile-photo requests start from these two.
BI

Reply to #general...

Full interactive demo coming soon at demo.boardbox.app

Real outcomes

The product is bigger than memory. It changes what the AI is able to do on turn one.

Advice starts from your actual situation

A health agent can load health plus general profiles. A finance agent can load company context and Stripe data. The answer starts specific.

Context does not bleed everywhere

Work, health, dating, faith, and finance stay separate by default. The agent can bridge domains intentionally, but one stray detail does not become global truth.

The AI can be opinionated without being reckless

Specialist agents can be configured to challenge, commit, and reason from evidence instead of optimizing for agreeable chat.

The workspace compounds with use

Profiles evolve with approval, artifacts accumulate, media stays searchable, and indexes keep the map current for future conversations.

How it works

The architecture is the product.

Boardbox is not trying to be a prettier chat window. Chat is the surface. Underneath it is the structured representation that lets any strong model act less like a stranger and more like a specialist who knows the file.

The AI starts with the right picture of you

Profiles capture the parts of your life or company that matter, so a serious conversation does not begin with a context dump.

The right context stays in the right room

Health, dating, finance, product, and engineering each get their own space. A detail from one area only crosses over when it should.

Good answers become living work

Meal plans, specs, studies, briefs, and decision logs survive the thread as artifacts the agent can keep using.

The workspace has a current map

Indexes tell the agent what exists before it loads details, keeping context retrieval accurate instead of vague or expensive.

Cross-comparison

Boardbox is built around the failure modes serious AI users already feel.

This is not a model leaderboard. Better models make Boardbox better. The product exists because mass-market chat products do not give those models the structure they need to know you, challenge you, and keep durable work alive.

Failure mode

The AI agrees too easily when you sound confident

Boardbox countermeasure

Channel agents are designed for pushback, calibration, and domain-specific judgment
Bad assumptions get challenged before they become plans

Failure mode

One global memory smears unrelated parts of your life together

Boardbox countermeasure

Profiles are modular, workspaces are separate, and channels decide what context gets loaded
Dating context does not pollute engineering advice; finance does not leak into health

Failure mode

Every serious chat begins with a long context reconstruction prompt

Boardbox countermeasure

Profiles, artifacts, media, and indexes persist as structured workspace data
Turn one starts from what the system already knows

Failure mode

Useful outputs die in scrollback

Boardbox countermeasure

Plans, specs, analyses, and decisions become artifacts with summaries that feed the index
The workspace compounds instead of resetting every conversation

Failure mode

Images, screenshots, charts, and assets have to be re-uploaded again and again

Boardbox countermeasure

Media is persistent, described, tagged, searchable, and available through tool calls
Visual context becomes part of memory, not an attachment chore

Failure mode

Retrieval is vague search or stuffing everything into the prompt

Boardbox countermeasure

Deterministic indexes give agents a current map, then tools load only what matters
The product can grow without making every request noisy or expensive

Pricing

Priced for people who use AI seriously.

The architecture keeps query cost bounded because agents read indexes first and load only the context they need.

Bring your own key

$20/month

For API-key power users who want control over model choice and inference costs.

Full product access
Use your own LLM API keys
Profiles, artifacts, indexes, media
Personal and commercial workspaces

Managed

$40/month

For users who want Boardbox to manage inference with generous bounded quotas.

Managed model access
Specialized channel agents
Tool integrations
Multi-agent features as they ship

Founding lifetime

$199once

Capped launch cohort for early believers and product-shaping users.

Lifetime founding access
Locked early-member status
Direct product feedback loop
Best fit for serious early adopters
Request access