CommunicationOS

Machine intelligence

Models that run on the way in

Three instruments run on a message as it arrives, and the rest work on a schedule or when you open a thread. Deal terms come out, voice notes turn into text, and promotions get held back.

8

Instruments on ingest

42

Translation languages

350ms

Median processing time

0

Shared training pools

Core instruments

Eight instruments working inside the feed

Incoming messages pass through the chain in order. The instruments work out reply deadlines, catch promises made to a client and clear out noise, so your team reviews the conversations that matter.

01

Spam shield

Catches phishing links, crypto solicitations and bulk marketing drops before any notification fires.

Blocks 99.4% of automated cold spam at the gateway

02

Noise classifier

Separates two-factor codes, auto-replies and platform notifications from real conversations with buyers.

Routes verification codes to a throwaway sidecar tab

03

Thread summaries

Writes a four-bullet brief of a two-hundred-message group chat by the time you open the thread.

Rebuilt on every tenth inbound message

04

Commitment tracking

Pulls out promises like “I will send the revised quote by 4pm” and puts them on your calendar.

Flags an unfulfilled promise four hours before deadline

05

Reply debt

Counts the outstanding questions waiting on your answer across the networks you have connected.

Ranks unread contacts by historical trade volume

06

Relationship health

Watches for message frequency drops and tone shifts with long-term trading accounts.

Alerts the account owner when a weekly buyer goes quiet

07

Voice transcription

Turns an incoming voice note into plain text paragraphs the moment it lands in the thread.

Handles WhatsApp voice notes and regional audio formats

08

Media understanding

Reads text off photos of paper manifests, assay certificates, bank transfer slips and export documents.

Pulls invoice numbers and amounts straight into search

Writing assist

Draft replies in your own voice

Write faster while still sounding like yourself. The system reads your past outgoing messages and proposes replies that match your vocabulary and your punctuation.

Smart reply

Three context-aware reply options in one click, weighed against current inventory and open order status.

Inline autocomplete

Suggests the next four words as you type. Press Tab to accept the completion or keep typing to ignore it.

Voice reply

Speak your raw thoughts into the app on a walk. The engine cleans the audio into a formatted business note.

Live translation

Talk to international suppliers in their language while reading and typing in your own. Forty-two languages.

Live translation, 42 languages

The customer writes in Arabic, you read it in English, you type your answer in English, and they receive Arabic. Both the original text and the translated version stay in the thread.

received • ar

هل وصلت الشهادة؟

“Did the certificate arrive?”

sent • en → ar

“Yes, emailed this morning.”

PersonaLearn studies your past replies to write a full message in your voice. It has its own page, and its own privacy rules.

How PersonaLearn works

Media understanding

Read documents inside incoming images

Clients snap photos of diamond grading reports, customs declarations and bank receipts rather than sending a clean PDF. The media engine pulls the serial numbers, the amounts and the stamps out of the picture so you can search them later.

Assay certificates

Extracts carat weights, cut grades and lab numbers from phone camera snaps.

Wire receipts

Pulls sender name, IBAN and total sum from mobile banking screenshots.

Shipping manifests

Reads stamped paper airway bills and matches tracking codes to open deals.

Voice memos in dialect

Transcribes hurried voice notes recorded in noisy trade halls and ports.

Safe deployment

Test the AI in shadow mode

A model should not reply to a real customer until you have checked its work. Shadow mode replays your last five hundred closed conversations through the engine in a sandbox. You read each proposed draft next to what your team sent, then decide.

1

Pick the history

Select five hundred closed threads from WhatsApp, Telegram, Signal or email.

2

Run the simulation

The engine processes every inbound turn and drafts a response in the background.

3

Read the report

See where the model matched your team, where it held back and where it was wrong.

4

Turn on live assist

Enable suggested drafts for your staff with the confidence thresholds you verified.

Replay, 500 conversations

simulation
Would have sent418
Would have held for a human74
You would have changed8

Five hundred threads replayed. 418 matched what your team sent, 74 were held for a human, 8 you would have rewritten.

98.1% of the 426 send decisions needed no edit

Data boundaries

Your communication data stays private

Messages are processed inside your own tenant. Trading terms, contact details and price negotiations never enter a public training set or a shared model memory.

Base model training excluded

Your messages are never used to train a base model for us, for Anthropic, or for anyone else.

No multi-tenant data pooling

Data from your workspace is separated at the database level and never combined with another company's records.

No human message review

Our engineers cannot read your inbox contents or open your attachments while working a support ticket.

Isolated custom keys

Bring your own provider keys so inference runs under your own enterprise agreements.

Ephemeral prompt handling

Inference requests are discarded once processed. Nothing lingers on an intermediary cache server.

Where it runs

Models execute in dedicated European instances. Encryption keys stay in your custody through bring-your-own-keys.

Security detail

Run triage on every channel

Start with a five-hundred-conversation shadow run. Read the output before your team sends a single live message.

No card required. Production deployment takes under an hour.

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