Omnesis Brain

Architecture

From context substrate
to cognitive substrate

The context substrate is the ground truth. It is factual and it does not interpret. But raw retrieval is not understanding. The Omnesis Brain aims to derive the deeper meaning of the things in your life, and to enable intelligence that is proactive rather than reactive.

Collector

Supports 40+ sources

Context substrate

Omnesis materializes your digital life into a searchable people and document graph

Omnesis Brain

Background agent

Reacts to mutations in your context substrate to maintain the derived substrate.

Sweeps

Recipes for pattern finding and periodic reviews on their own cadence. Sweeps can be contributed by the community.

Derived substrate

Time index

Extract semantic times and ranges buried in your context substrate into a queryable index.

Document annotations

Annotate your documents with deeper insights.

People annotations

Annotate the people in your life with learned insights (relationships, roles, etc.)

Open loops

Understand all the unresolved things in your life: decisions you need to make, actions you need to take, commitments made by you or owed to you, etc.

Briefs

The Omnesis Brain can choose to bring something to your awareness via a “brief” in the companion app.

Sweeps

Sweeps: recipes for
recurrent reflection

Some things about your life are only visible from a distance — changes in health, finance or relationship patterns. Sweeps let a background agent step back and look for those patterns, at a cadence you define.

1 --- 2 name: Day ahead 3 cadence: 1d 4 at: "05:00" 5 --- 6 7 Prepare the user for the day that is starting. Look at what is happening today — meetings, appointments, scheduled events — and for the ones that merit it write an informative brief: what it is, when, with whom, and the context worth having to hand, drawn from the surrounding correspondence. Stamp each brief with the time of the event it concerns so the feed can rank it into the right part of the day, and cite the documents you drew it from. Check the open loops falling due today or very shortly and remind the user where a reminder would help. Then look a week out — across both source-owned schedules and your own recorded interpretations of upcoming time — and for anything genuinely approaching that needs preparing, surface it and open a loop if it is a real obligation nobody is tracking yet. If along the way you find a tracked obligation has already been fulfilled — a receipt, a confirmation, a reply that settles it — close its loop as done with a note and remove the briefs it made moot; never delete a loop that was actually completed, because the record of what happened is worth keeping. Check what is already in the feed before writing anything, so an earlier pass's card is updated rather than duplicated. Where an event later today would benefit from the freshest possible picture, schedule yourself a short follow-up shortly beforehand to rebuild its brief. Most days only a handful of things merit a brief, and an empty pass is a fine outcome.

sweeps/may-day.md

Briefs

Briefs: when the Brain
decides to speak

A brief is the Omnesis Brain deciding to tell you something. It can be a briefing about what you need to know for your next meeting, a summary of your day to come, a reminder to top up a bank account that’s about to go negative, or anything else identified by one of your sweeps. You can engage with a brief by responding to it, which opens a new conversation with Omnesis.

A brief open in the Omnesis app: resting heart rate up and HRV down against the person's own baseline, after four hard sessions and short nights, citing Apple Health documents

Tell Omnesis

Tell the brain,
while on the go

Any context you want to quickly tell the Omnesis Brain? Speak it or type it, directly via the app or via Siri. Say it once, and let it go. Trust that the brain will absorb it and consolidate. Your note is enriched with important metadata: when you said it, where you were when you said it, and what you were doing when you said it.

An Apple Watch listening: “Hey Siri, Omnesis Capture — what should I remember?”, with the spoken line “Jameel just said he’s send me the revised quote by Friday”

Watches

Watch Engine: detect conditions
expressed in natural language

Ask Omnesis to be notified when a certain condition is met. Omnesis compiles your condition expressed in natural language into a DSL evaluated by the Watch engine.

Tell me when I receive an email about a property listing and I have not replied in 3 days.

1 { 2 "watch": { 3 "name": "x-listing-unanswered", 4 "nl_query": "Tell me when I receive an email about a property listing and I have not replied in 3 days.", 5 "firing_policy": "stays_active", 6 "ontology_fingerprint": "eef3032ba8488f3e61a908f6b28f5832", 7 "nodes": [ 8 { 9 "id": "listing", 10 "type": "source.document_event", 11 "filter": { 12 "source": "gmail", 13 "event": [ 14 "created" 15 ], 16 "documentType": "email", 17 "people": [ 18 { 19 "role": "sender", 20 "isSelf": false 21 } 22 ] 23 }, 24 "recall": { 25 "semantic": { 26 "query": "property listing, a house or flat for sale or to rent, with an asking price or a viewing", 27 "threshold": 0.35 28 } 29 }, 30 "judge": { 31 "proposition": "This email is about a specific property being offered for sale or to rent — a listing, a viewing, or an agent's details for one — and it is addressed to the recipient rather than a mass mailing", 32 "output_schema": { 33 "why": "string" 34 } 35 }, 36 "output_map": { 37 "doc_id": "$e.docId", 38 "thread_id": "$e.metadata.extra.threadId", 39 "why": "$judge.why" 40 } 41 }, 42 { 43 "id": "my_reply", 44 "type": "source.document_event", 45 "filter": { 46 "source": "gmail", 47 "event": [ 48 "created" 49 ], 50 "documentType": "email", 51 "people": [ 52 { 53 "role": "sender", 54 "isSelf": true 55 } 56 ] 57 }, 58 "output_map": { 59 "thread_id": "$e.metadata.extra.threadId" 60 } 61 }, 62 { 63 "id": "unanswered", 64 "type": "stateful.wait", 65 "inputs": { 66 "listing": { 67 "role": "arm", 68 "key": { 69 "thread_id": ".thread_id" 70 } 71 }, 72 "my_reply": { 73 "role": "cancel", 74 "key": { 75 "thread_id": ".thread_id" 76 } 77 } 78 }, 79 "on_collision": "reset", 80 "duration": "3 days", 81 "output_map": { 82 "doc_id": "$n.listing.doc_id", 83 "why": "$n.listing.why" 84 } 85 } 86 ], 87 "sink": { 88 "input": "unanswered", 89 "output_map": { 90 "evidence": "$n.unanswered.doc_id", 91 "why": "$n.unanswered.why" 92 } 93 }, 94 "delivery": { 95 "kind": "omnesis-notify" 96 } 97 } 98 }

watches/x-listing-unanswered.json

source.document_event listing source=gmail · event=created LLM judgesemantic recall

source.document_event my_reply source=gmail · event=created

stateful.wait unanswered 3 days after arming collision: reset

sink from unanswered Notifies your devices omnesis-notify

(thread_id)

(thread_id)cancels

Tell me when sleep, HRV and heart rate all deviated from my usual on the same day.

1 { 2 "watch": { 3 "name": "x-body-signal-day", 4 "nl_query": "Tell me when sleep, HRV and heart rate all deviated from my usual on the same day.", 5 "firing_policy": "stays_active", 6 "ontology_fingerprint": "eef3032ba8488f3e61a908f6b28f5832", 7 "nodes": [ 8 { 9 "id": "morning_tick", 10 "type": "source.time", 11 "recurring": "0 9 * * *", 12 "output_map": { 13 "due_at": "$e.dueAt" 14 } 15 }, 16 { 17 "id": "sleep_dev", 18 "type": "sql", 19 "inputs": { 20 "morning_tick": { 21 "role": "arm" 22 } 23 }, 24 "query": "WITH daily AS (SELECT cast(start_time AS DATE) AS day, avg(value) AS v FROM health_sleep WHERE metric_slug = 'asleep_minutes' GROUP BY 1), subject AS (SELECT v FROM daily WHERE day = $today - INTERVAL 1 DAY), baseline AS (SELECT avg(v) AS avg_v, count(*) AS n_days FROM daily WHERE day BETWEEN $today - INTERVAL 31 DAY AND $today - INTERVAL 2 DAY) SELECT ($today - INTERVAL 1 DAY) AS day, baseline.n_days >= 14 AND abs(subject.v - baseline.avg_v) >= 0.30 * baseline.avg_v AS fires, round(100.0 * (subject.v - baseline.avg_v) / baseline.avg_v, 1) AS deviation_pct FROM subject, baseline", 25 "output_map": { 26 "day": "day", 27 "deviation_pct": "deviation_pct" 28 } 29 }, 30 { 31 "id": "hrv_dev", 32 "type": "sql", 33 "inputs": { 34 "morning_tick": { 35 "role": "arm" 36 } 37 }, 38 "query": "WITH daily AS (SELECT cast(start_time AS DATE) AS day, avg(value) AS v FROM health_vitals WHERE metric_slug = 'hrv' GROUP BY 1), subject AS (SELECT v FROM daily WHERE day = $today - INTERVAL 1 DAY), baseline AS (SELECT avg(v) AS avg_v, count(*) AS n_days FROM daily WHERE day BETWEEN $today - INTERVAL 31 DAY AND $today - INTERVAL 2 DAY) SELECT ($today - INTERVAL 1 DAY) AS day, baseline.n_days >= 14 AND abs(subject.v - baseline.avg_v) >= 0.45 * baseline.avg_v AS fires, round(100.0 * (subject.v - baseline.avg_v) / baseline.avg_v, 1) AS deviation_pct FROM subject, baseline", 39 "output_map": { 40 "day": "day", 41 "deviation_pct": "deviation_pct" 42 } 43 }, 44 { 45 "id": "hr_dev", 46 "type": "sql", 47 "inputs": { 48 "morning_tick": { 49 "role": "arm" 50 } 51 }, 52 "query": "WITH daily AS (SELECT cast(start_time AS DATE) AS day, avg(value) AS v FROM health_vitals WHERE metric_slug = 'heart_rate' GROUP BY 1), subject AS (SELECT v FROM daily WHERE day = $today - INTERVAL 1 DAY), baseline AS (SELECT avg(v) AS avg_v, count(*) AS n_days FROM daily WHERE day BETWEEN $today - INTERVAL 31 DAY AND $today - INTERVAL 2 DAY) SELECT ($today - INTERVAL 1 DAY) AS day, baseline.n_days >= 14 AND abs(subject.v - baseline.avg_v) >= 0.30 * baseline.avg_v AS fires, round(100.0 * (subject.v - baseline.avg_v) / baseline.avg_v, 1) AS deviation_pct FROM subject, baseline", 53 "output_map": { 54 "day": "day", 55 "deviation_pct": "deviation_pct" 56 } 57 }, 58 { 59 "id": "all_three", 60 "type": "stateful.and", 61 "inputs": { 62 "sleep_dev": { 63 "role": "arm", 64 "key": { 65 "day": ".day" 66 } 67 }, 68 "hrv_dev": { 69 "role": "arm", 70 "key": { 71 "day": ".day" 72 } 73 }, 74 "hr_dev": { 75 "role": "arm", 76 "key": { 77 "day": ".day" 78 } 79 } 80 }, 81 "deadline": "1 day", 82 "on_collision": "ignore", 83 "output_map": { 84 "sleep_pct": "$n.sleep_dev.deviation_pct", 85 "hrv_pct": "$n.hrv_dev.deviation_pct", 86 "hr_pct": "$n.hr_dev.deviation_pct" 87 } 88 } 89 ], 90 "sink": { 91 "input": "all_three", 92 "output_map": { 93 "sleep_pct": "$n.all_three.sleep_pct", 94 "hrv_pct": "$n.all_three.hrv_pct", 95 "hr_pct": "$n.all_three.hr_pct" 96 } 97 }, 98 "delivery": { 99 "kind": "omnesis-notify" 100 } 101 } 102 }

watches/x-body-signal-day.json

source.time morning_tick cron 0 9 * * *

sql sleep_dev DuckDB over your analytics

sql hrv_dev DuckDB over your analytics

sql hr_dev DuckDB over your analytics

stateful.and all_three every arm, within 1 day collision: ignore

sink from all_three Notifies your devices omnesis-notify

(day)

Tell me when an unusually large payment is made and it can't be explained by a bill I received or a subscription.

1 { 2 "watch": { 3 "name": "x-unexplained-large-payment", 4 "nl_query": "Tell me when an unusually large payment is made and it can't be explained by a bill I received or a subscription.", 5 "firing_policy": "stays_active", 6 "ontology_fingerprint": "eef3032ba8488f3e61a908f6b28f5832", 7 "nodes": [ 8 { 9 "id": "spend", 10 "type": "source.analytics_row", 11 "table": "bank_transactions", 12 "op": [ 13 "inserted" 14 ], 15 "predicate": "amount < 0", 16 "output_map": { 17 "txn_key": "$e.row.transaction_key", 18 "amount": "$e.row.amount", 19 "currency": "$e.row.currency", 20 "merchant": "$e.row.merchant_name" 21 } 22 }, 23 { 24 "id": "above_p99", 25 "type": "sql", 26 "inputs": { 27 "spend": { 28 "role": "arm" 29 } 30 }, 31 "query": "WITH baseline AS (SELECT quantile_cont(abs(amount), 0.99) AS p99, count(*) AS n_txns FROM bank_transactions WHERE amount < 0 AND currency = $n.spend.currency AND transaction_key <> $n.spend.txn_key AND transaction_date BETWEEN $today - INTERVAL 30 DAY AND $today) SELECT baseline.n_txns >= 14 AND abs(CAST($n.spend.amount AS DECIMAL(18,4))) > baseline.p99 AS fires, round(baseline.p99, 2) AS p99 FROM baseline", 32 "output_map": { 33 "p99": "p99" 34 } 35 }, 36 { 37 "id": "explained", 38 "type": "llm", 39 "mode": "investigation", 40 "inputs": { 41 "above_p99": { 42 "role": "arm" 43 } 44 }, 45 "proposition": "This charge is explained by something already in the corpus: a bill or invoice received for it, or a recurring subscription with proof of it — a confirmation, a renewal notice, or earlier charges of the same shape from the same merchant.", 46 "output_schema": { 47 "explained": "bool", 48 "proof": "string" 49 }, 50 "fire_when": "NOT explained", 51 "scope": { 52 "horizon": "180 days" 53 }, 54 "budget": { 55 "tool_calls": 12, 56 "tokens": 40000 57 }, 58 "output_map": { 59 "proof": "proof" 60 } 61 } 62 ], 63 "sink": { 64 "input": "explained", 65 "output_map": { 66 "evidence": "$n.spend.txn_key", 67 "merchant": "$n.spend.merchant", 68 "proof": "$n.explained.proof" 69 } 70 }, 71 "delivery": { 72 "kind": "omnesis-notify" 73 } 74 } 75 }

watches/x-unexplained-large-payment.json

source.analytics_row spend table=bank_transactions op=insertedpredicate=amount<0

sql above_p99 DuckDB over your analytics

llm explained deliberates with tools LLM investigationhorizon 180 days

sink from explained Notifies your devices omnesis-notify

Agents

Watches can wake your external agent
and trigger workflows

Your external agent can ask Omnesis to watch for something. When the condition is met Omnesis wakes the agent so it can pull the necessary context (via Omnesis privacy gate) and run its workflow — no polling.

Openclawonline

any time I receive a new property listing by email, crawl it, confirm 2 bedrooms and under 30 min from work, then ping me here09:12

Sure thing, let me ask Omnesis to create a watch!09:12

create watch

Inbox

2-bed flat, Maple Court

Nora T.to me 14:47

hi Maya, sending over one new property that just got into the market…

watch fires

wake agent

read email
crawl listing
check commute
draft message

Openclawonline

Sonia sent you a property listing with 2 beds that’s a 15 min walk from work!14:49

From context substrate to cognitive substrate

Background agent

Sweeps

Time index

Document annotations

People annotations

Open loops

Briefs

Sweeps: recipes for recurrent reflection

Briefs: when the Brain decides to speak

Tell the brain, while on the go

Watch Engine: detect conditions expressed in natural language

Watches can wake your external agent and trigger workflows

From context substrate
to cognitive substrate

Sweeps: recipes for
recurrent reflection

Briefs: when the Brain
decides to speak

Tell the brain,
while on the go

Watch Engine: detect conditions
expressed in natural language

Watches can wake your external agent
and trigger workflows