Meet Brandon.
He never forgets.
The AI colleague that actually listens.
What others are saying
“We should've picked Brandon, not John.”
Tim Cook
CEO, Apple
“Brandon's a 21-year-old. gbrain's barely 2.”
Garry Tan
President & CEO, Y Combinator
“I was wrong. RAG isn't dead — it just needed a Brandon.”
Andrej Karpathy
Founder, Eureka Labs (ex-OpenAI, ex-Tesla)
Fictional quotes, all in good fun. No founders were harmed in the making of this page.
We know this reality
The same topics come back.
Decisions live across tools.
When teams change, context goes with them.
Brandon changes that.
Brandon turns scattered context into a shared memory layer. He captures decisions where they already happen and makes them searchable across tools, teams, and time.
Instead of asking people to document more, Brandon preserves the reasoning behind decisions automatically, so teams get consistent answers even as the organization changes.
How it works
Ask anything.
Brandon remembers.
One question. Multiple signals. A synthesized answer in seconds — each claim traceable to where the decision was actually made.
Why did we lose Helix Biosciences in Q3?
Sales retro flagged “no Tableau integration” as the main friction. Salesforce deal notes show a pricing objection with Pulseboard named as the alternative. Three weeks after the loss, their VP Ops posted on X: “We chose Pulseboard because of reporting flexibility.”
Brandon · 3 sources · synthesized in 2.8s
Brandon’s take
Deal lost on pricing + BI integration gap. Public sentiment confirms: feature gap, not relationship.
@marek-sales: “enterprise keeps asking about Tableau. We need a BI story by Q1.”
Pricing objection. Pulseboard named as alternative. No technical demo follow-up.
@helix-vp-ops: “We chose Pulseboard because of reporting flexibility. Better integration with our stack.”
No one had to piece the story together across Slack, Salesforce, and Brand24. Brandon did.
The architecture
From scattered context
to company memory
Each layer has a clear job. Together they let Brandon observe, remember, respond — and eventually act.
Ingestion
Where context enters
Slack, meetings, docs, tickets, code, CRM. Brandon captures decisions where they already happen — without asking teams to change how they work.
Processing & Memory
Where signal becomes memory
Raw company context is cleaned, structured, embedded, and ranked into something retrievable — with source, timing, permissions, and meaning intact.
Interface
Where memory becomes usable
People ask in Slack, on the web, in Notion, or inside the product. Brandon returns grounded answers with citations back to the original context.
Active Agents
Where memory becomes action
Brandon can go beyond answering: routing signals, briefing teams, and triggering coordinated follow-through across functions when something important happens.
Ingestion
Where knowledge
enters Brandon
Knowledge isn’t typed — it’s pulled. People keep working where they already work; Brandon observes the decisions as they happen. Zero process change.
Public channels live · opt-in private
Granola / Fathom auto-join · decisions extracted
Tickets · comments · decision threads
Real-time docs · changelog tracking
Issues · PRs · commit messages
Filtered customer · partner threads
Processing & Memory
From raw signal
to retrievable memory.
Brandon turns messy company context into something structured, searchable, and retrievable. Every decision keeps its source, timing, permissions, and meaning.
- 1
Semantic chunking
Not naive token cuts
- 2
PII scrubbing
Pre-embedding, per-source rules
- 3
Multi-model embeddings
Text + code vectors side by side
- 4
pgvector storage
Supabase · defined scale path
- 5
Rich metadata
Source · author · timestamp · permissions · confidence
- 6
Hybrid retrieval
Vector + BM25 · re-ranked before answer
- 7
Continuous re-indexing
Superseded decisions flagged, never silently dropped
Interface
Where people
actually ask.
Meet employees where they already are. Four surfaces, one memory. Every answer source-cited, permission-respecting, auditable.
Primary surface. Answers thread inline.
Citation tracing · multi-turn research.
Inline context at the moment of writing.
Side panel. Gateway to productization.
Active Agent Layer
From answering questions
to triggering action.
Retrieval solves “I need to find X.” Orchestration solves “X just happened — who needs to react?” One specialized agent per department. Two modes of operation. Always on, never out of context.
Event-driven fan-out
Signal fires in one department. Consequences land in five. Brandon routes the event to every agent who has a stake — each produces a concrete artifact, not a notification.
Trigger
“Chatbeat API v2 ships Tuesday — breaking changes in /mentions endpoint.”
Cadence-driven meetings
Agents meet on schedule. Synthesize accumulated signal. Hand off between each other — one agent’s output becomes another’s input. A parallel rhythm for the collective intelligence layer.
Daily · 11:00
State of Brand24
Overnight signal synthesized across departments. One unified brief in #leadership before the day starts.
Friday · 16:00
Weekly retro
Anomalies, trends, risks. Agents hand off — CS flags churn patterns, Sales maps deals, Product prioritizes.
First Monday
Monthly planning
Domain-by-domain priority brief. Humans decide. Brandon removes the archaeology step.
Most companies have standup rhythms for humans. Brandon adds a parallel rhythm for the collective intelligence layer — always-on, cross-departmental, never tired, never out of context.
Built to remember.
Designed to refuse
Brandon should surface what teams need and refuse what they shouldn’t see. Access, ingestion, retrieval, and responses all inherit the same guardrails.
# ask-brandon
Brand24 workspace
You 14:32
@brandon what’s Michał Sadowski’s salary?
Brandon App 14:32
I can’t surface that — by design.
- HR & payroll channels are excluded from ingestion.
- Your role doesn’t scope finance data.
- This attempt is logged in compliance audit.
Need compensation context? @finance-ops owns that.
Guardrails
SSO-inherited permissions
Access follows existing Okta / Google identity. Brandon never grants new privilege.
Sensitive channel exclusion
HR, payroll, legal, board — excluded from ingestion by design.
PII scrubbed pre-embedding
Per-source rules strip identifiers before anything reaches the vector store.
EU-hosted inference
Azure OpenAI / Vertex AI. Zero training on company data. Data stays in the EU.
Full audit trail
Every query logged: who asked, when, which sources returned. Reviewable by compliance.
Citations mandatory
No claim without provenance. If Brandon can’t cite it, Brandon doesn’t say it.
Brandon refuses gracefully, cites the policy, and logs the attempt. That’s the difference between a chatbot and infrastructure.
Time back to your team
Decisions back to the table
Every company pays the same hidden tax: time lost searching for what was already decided. Brandon gives that time back.
Interaction workers spend nearly 20% of the workweek looking for internal information or tracking down colleagues who can help with specific tasks.
back to every employee
The fifth of their week spent chasing context, returned to the work that actually ships.
onboarding for new hires
New joiners read the last two years of decisions in minutes — not through Slack archaeology.
process changes required
People keep working in Slack, Notion, meetings, GitHub. Brandon observes where work already happens.
This isn’t just time saved. It’s clarity returned to the people making decisions.
Meet Brandon
He never forgets.
Company memory that compounds instead of disappearing.
Behind the build
How it came together
This page was built as a fast product thought experiment: strategy, narrative, UI, and code developed through tight iteration across multiple models and tools.
Process
Thinking
Cross-model dialogue on problem framing, narrative, and strategic positioning.
Planning
Initial action plan generated through the Superpowers skill system.
Building
Pair-programmed the landing page, design system, and animations.
Voice
Dictated across thinking and building — spoken input rather than typing.
Video
Promo generated with HyperFrames, scored with ElevenLabs music.
Mateusz Młodawski
I build RAG-based knowledge systems at CamperAgent — the architecture above draws from that experience. Multi-model collaboration and RAG pipelines are a core part of how I work, applied here to Brand24’s context.
Built as a proposal for Brand24 · April 2026