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Real-Time Data Sharing
in Financial Markets
Instantly and securely share live trading data with all permissioned users and channels, ensuring full control and eliminating manual file handling and duplication.
What is Real-Time Data Sharing?
Real-time data sharing means delivering live data to the right people, tools and channels the moment it changes, with full control over who can see it. ipushpull provides a secure layer that connects your data sources to spreadsheets, apps and chat platforms so trading teams can collaborate on live information without files, copy-paste or delay. Real-time data sharing is the foundation of chat-based workflow automation for trading.
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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 real-time data sharing solves
Markets move faster than traditional handoffs. When data is passed via files, screenshots or manual messaging, four problems show up immediately:
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- Latency
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- Version drift & operational risk
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- Data lineage & coverage
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- Control gaps
Real-time sharing removes these failure points by making live data the default object in every workflow.
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How ipushpull delivers real-time data
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- Connect your data sources (Excel models, internal systems, pricing engines, reference data, APIs).
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- Permission the data at dataset, row or field level based on user roles and entitlements.
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- Publish live views into the channels your teams and clients already use: Excel, web apps and enterprise chat.
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- Synchronise changes promptly across all connected locations.
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- Audit every view, share, update and workflow action with timestamps and metadata.
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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. Live prices, RFQs, axes, and workflow outputs can be published into enterprise chat channels as permissioned objects. Updates propagate in real time, so the thread always reflects the 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.