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Real-time data sharing
for financial markets
Publish live prices, axes and RFQs once, and every permissioned trader, client and system sees the same numbers, in chat, Excel or an app.
What is real-time data sharing?
Real-time data sharing delivers a live dataset to the people and systems entitled to see it, and updates every copy the moment the source changes. On a trading desk that means quotes in chat match the pricing model, a client's Excel sheet shows the current axe, and nobody emails a file.
ipushpull connects your sources (Excel models, pricing engines, internal systems and APIs) and publishes permissioned live views into Bloomberg, Symphony, Microsoft Teams, WhatsApp, Slack, Telegram, WeChat, LSEG Messenger, Excel and web apps.
NatWest Markets digitised its trade axes with ipushpull so clients never work from outdated data. Read the NatWest Markets case study.
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Share live prices, axes, RFQs and market colour across desks and counterparties in seconds
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Keep a single permissioned source of truth across Excel, chat and downstream systems
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Maintain auditability and control in regulated trading environments
What breaks when data moves by file
Stale quotes: a price pasted into chat at 09:00 is still there at 09:20, after the model has moved.
Versions drift: three desks hold three copies of the same axe sheet, and each has been edited.
Lost lineage: once a screenshot leaves the desk, nobody can say where the number came from.
No control: attachments go to whoever is in the chat room, entitled or not.
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How it works
1. Connect a source: an Excel range, a pricing engine, a database or an API.
2. Set who can see what, by dataset, row or field.
3. Publish a live view into chat, Excel or a web app.
4. Every connected copy updates when the source changes.
5. ipushpull records each view, share and update with a timestamp.
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What can be shared
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- Live price streams and quote grids
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- Axes, IOIs, inventory summaries
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- RFQ details and negotiation state
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- Market colour and desk updates
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- Trade details and booking status
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- Risk/limits snapshots for approvals
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- Reference data and static enrichment fields
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Where this gets used in trading workflows
Chat-based workflow automation for trading. Trigger, route, and govern trading workflows directly from chat.
Trade capture and booking automation in trading markets. Convert chat negotiations and RFQs into structured trades pushed to booking systems.
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Outcomes for Trading Firms
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Operational
Shorter time from request to quote and quote to booking.
Reduced manual formatting and spreadsheet handoffs.
Fewer reconciliation breaks from inconsistent data.
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Commercial
Faster response windows to RFQs and chat-based requests.
Greater consistency in price distribution across channels.
Better capture of client interest and intent.
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Control & Compliance
Data distribution aligned to entitlements.
Full audit trails of what was shared, when, and by whom.
Reduced uncontrolled attachment and screenshot sharing.
Financial markets use cases
Live pricing into chat
Live pricing into chat
Problem: quotes in chat lag behind Excel models.
ipushpull workflow: publish Excel ranges as live objects in chat.
Result: quotes stay current without constant manual intervention.
Real-time axes across desks
Real-time axes across desks
Problem: axes distributed as stale snapshots.
ipushpull workflow: permissioned live feed into Excel and chat.
Result: sales and traders operate on one view.
Live risk checks for approval
Live risk checks for approval
Problem: manual risk screenshots slow approvals.
ipushpull workflow: real-time risk windows embedded in approval threads.
Result: faster approvals with audit.
Frequently asked questions
What is real-time data sharing in financial markets?
Delivering live trading data as a single, continuously updated source to multiple users and channels at the moment it changes. Everyone works from the same data object, not separate snapshots, with permissions and audit applied at source.
Is my data secure?
Yes - ipushpull is ISO 27001 certified. Your data is secure and is encrypted in flight and when at rest. ipushpull uses encryption in transit between your applications or service and your ipushpull service and between your ipushpull service and any end-user client application. Any data stored in your ipushpull database is also encrypted.
How does real-time data sharing support AI or LLM workflows?
AI tools in markets rely on access to current, governed data. Real-time sharing lets authorised agents or users query live datasets and feed outputs back into chat or systems through audited workflows, so automation doesn’t bypass control or compliance.
Can real-time data be delivered into chat?
Yes. ipushpull publishes live prices, RFQs, axes and workflow outputs into Bloomberg, Symphony, Microsoft Teams, WhatsApp, Slack, Telegram, WeChat and LSEG Messenger as permissioned objects. Updates arrive as the data changes, so the thread always shows current data.
Can data be shared into chat and Excel simultaneously?
Yes. The same live dataset can be published into Excel, web apps, and enterprise chat at the same time. Updates made in any location synchronise instantly across all others, without files or copy-paste.
Does real-time sharing require changes to existing systems?
No major rebuild. ipushpull connects to existing pricing engines, internal systems, and spreadsheets through APIs or webhooks, then layers permissioning, delivery, and audit on top of what you already run.