"Who's at the center of my world?"
Find the most-connected entities — the person at the hub of every project, the property linked to half your finances, the vendor showing up across years.
Platform · Knowledge becomes time-aware reasoning
One timeline. Multiple sources. Bi-temporal from day one.
Most personal databases think in records-as-strings. Lossless thinks in records-as-events with both occurred-at and known-at timestamps — so a charge that posts three days after the swipe doesn't break the chronology, and an amended tax return doesn't overwrite the original. Vehicle service, statements, voice notes, emails, toll charges, charging sessions — one timeline, multiple sources, every event sealed.
← Five tracks, one timeline
Bi-temporal · occurred-at + known-at
Every dot opens to its sealed record →
01 — A real chronology: voice + finance + vehicle, woven into one timeline.
Why chronology matters
Search is a flat list.
Search is a flat list.
Chronology has gravity.
Most apps show you a flat list of search results. Chronology shows you what was happening — the recall notice that arrived two days before the service appointment that explains the zero-dollar charge. The plumber voice note that became the invoice that became the bank charge.
Lossless's chronology is the canonical view of your records, organized by when things actually happened — not when you remembered to file them.
- ✓ Mix vehicle, finance, email, voice, and document records on one axis
- ✓ Filter by entity ("just the Y," "just the Pine Ave duplex")
- ✓ Zoom: decade → year → month → day → minute
- ✓ Two-finger pinch on iPad / scroll-wheel on Mac
- ✓ Each event opens to its full record + cited sources
Worked example
What April looked like for one car.
APR 30 ·26
VEHICLE · MILEAGE
Month total: 1,420 mi · 89% home charging
APR 12 ·26
APR 10 ·26
APR 08 ·26
APR 04 ·26
APR 01 ·26
02 — One car, one month. The recall on Apr 1 is what scheduled the Apr 12 service, which closed the open ticket.
Filtering & entity scope
Every record knows what it's about.
Filter chronology to one entity — a vehicle, an account, a person, a property — and watch the timeline collapse to just what's relevant.
Filter
"Just the Y"
3,402 events. Service, charging, FasTrak, registration, insurance — nothing else.
Filter
"Just Pine Ave"
All maintenance, tenant comms, insurance, mortgage, property tax — for one address.
Filter
"Just Maria"
Every email, iMessage, Venmo, calendar event involving one person — chronologically.
The other axis
Chronology is one axis. The relationship graph is the other.
Every record in Lossless has a date and a place in a knowledge graph. The timeline answers "when?". The graph answers "how is this connected?". Together they're chronology in three dimensions — temporal on one axis, relational on the other.
Walk a person to the companies they work at, to the properties those companies own, to the loans on those properties, to the bank account paying those loans. Every hop is a verifiable edge. Every node is an entity Lossless extracted from your records.
REF · "GRAPH DATABASE: ENTITY RELATIONSHIPS" — VC PITCH DECK
EXAMPLE WALK
👤
Person · "John Smith"
extracted from email + calendar + iMessage
↓ WORKS_AT
🏢
Organization · Acme Corp
extracted from emails + LinkedIn
↓ OWNS_PROPERTY
📍
Property · 123 Main St
extracted from county records + lease
↓ HAS_MORTGAGE
💳
Account · PNC Loan #4521
extracted from mortgage statement PDF
An auto-extracted entity graph in the same RLS-protected Postgres as your records. Every edge is verifiable; every node cites its source records.
Graph analytics
Four questions you can only ask once your records have a graph.
"Which clusters are forming?"
Auto-discover natural clusters of entities — a household, a neighborhood, a friend group, a business circle — surfaced from the records, not declared.
"How am I connected to this?"
The shortest path between any two entities in your graph. From a stranger's name in an email to the mutual contact, business, or shared event that explains the connection.
"What ripples outward?"
Track how a change to one entity cascades — a renovation that touches a property, a tenant, a lease, a P&L line, an insurance policy, and a tax form.
SUPPORTED ENTITY TYPES
👤 Person · contacts, parties
🏢 Organization · companies, banks
📍 Location · addresses, places
💳 Financial · accounts, loans, cards
🏠 Property · real-estate, units
🚗 Vehicle · cars, trips, services
📅 Event · trips, appointments, festivals
📦 Asset · objects, gear, devices
"Bi-temporal stamping is the part you only appreciate the first time you have to reconstruct what was knowable as of a specific date — an amended return, a deposition, a discovery request. Once you've needed it, you stop accepting last-write-wins."
— Technical evaluator · tax-and-family-law cross-practice
Continue the architecture tour
You've seen the axes. Now see who else reads them.
Next pillar: the Agent API. How Claude, GPT, Gemini, Apple Intelligence — or your own agents — read from this same ledger under per-scope consent, with every read written to the audit log.