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Step by Step

How It Works

No setup project. No documentation sprint. Workipedia learns from the work your team is already doing — and gets better every day.

01

Connect Your Sources

Workipedia connects to the channels your team already uses — phone system, email inboxes, messaging, calendar. No migration, no new tools to learn. The work keeps happening the way it always has.

workipedia ~ step 01
> workipedia connect --sources
Connecting: phone (Twilio)
Connecting: email (IMAP)
Connecting: messages (SMS + web)
Connecting: calendar (Google)
[OK] 4 sources connected
[OK] Observation mode active
02

The System Observes

As your team works — taking calls, sending messages, handling emails — Workipedia quietly observes. It watches how your best employees handle situations, what questions they ask, what information they look up, and what decisions they make.

workipedia ~ step 02
> workipedia observe --mode passive
Listening to calls...
> Terry asks gate_code before scheduling
> John confirms equipment_serial_number
> CSR checks preferred_contact_method
> Billing escalates payment > $500 to manager
[OK] 4 patterns captured today
03

Facts Are Extracted

From calls, messages, and emails, Workipedia extracts atomic facts — customer preferences, equipment details, scheduling rules, escalation triggers. Every fact traces back to its source: which call, which message, which moment.

workipedia ~ step 03
> workipedia extract --today
Processing 47 calls, 23 messages, 12 emails...
> fact: customer.jane_miller.gate_code = 1234#
> source: call_2026-05-21_14:32 @ 02:15
> fact: customer.jane_miller.pref_contact = SMS
> source: msg_thread_8847
> fact: equipment.AX-7721.next_service = 2026-06-15
> source: email_from_john@ops
[OK] 18 facts extracted, evidence linked
04

Experts Confirm Casually

The system doesn't ask employees to fill out forms. Instead, it prompts at natural moments — during a call, in the inbox, in the email sidebar. A quick thumbs up, a single correction, a yes-or-no. Lightweight signals, not documentation projects.

workipedia ~ step 04
> workipedia feedback --summary
12 facts confirmed by experts today
3 AI drafts edited (learned from corrections)
2 escalations marked correct
1 bad suggestion dismissed
4 calls flagged as high quality
[OK] 22 learning signals captured
[OK] No forms. No documentation project.
05

The Night Shift

When the office closes, Workipedia reviews the day. It finds patterns across calls, corrections, escalations, and missed signals. It proposes new schema fields, updates memory, identifies procedure candidates, and supersedes stale information.

workipedia ~ step 05
> workipedia synthesize --nightly
Window: 2026-05-21 00:00 to 23:59
Processing 142 calls, 89 messages, 34 emails...
> patterns detected: 8
> new facts proposed: 12
> schema updates proposed: 3 fields
> procedure candidates: 2
> stale memories superseded: 4
[STEWARD] 17 proposals queued for review
[OK] Business wakes up smarter tomorrow
06

Context Surfaces Where Needed

When an employee picks up a call or opens a message the next day, everything relevant appears: recent interactions, known preferences, open tasks, missing information. No searching, no asking around, no losing context between channels.

workipedia ~ step 06
> workipedia surface --customer jane_miller
Loading context...
> recent: estimate follow-up call (yesterday)
> task: scheduling pending (due 2d)
> pref: afternoon, SMS
> fact: gate code 1234#
> fact: equipment S/N AX-7721
> missing: confirm address for visit
[SURFACE] Context pack ready for cockpit
Timeline

The system compounds.

Workipedia doesn't require a setup period. It starts learning immediately and gets meaningfully better every week. By month two, the business has a living operating memory it never had before.

Day 1Sources connected. System begins observing.
Week 1First facts extracted. Basic customer memory forming.
Week 2-4Schema patterns emerge. Expert corrections compound.
Month 2Procedures detected. Context surfacing active. AI drafts improving.
Month 3+Feedback flywheel compounding. Business operating memory is real.

// The system gets smarter because the business keeps operating,
// not because the business pauses to document itself.