.png?width=1200&height=628&name=Blog%20header-1%20(27).png)
.png)
.png)
In a previous blog, we looked at the Capture layer. In this blog, we will review ipushpull's orchestration capability and how it effectively maps and brings structure to your chat data. Every day, across countless chat windows, brokers and traders talk about pricing, probe interest and test the waters. Then the day ends, the chats are archived and all that messy, valuable data drifts into history.
What if it didn’t?
ipushpull can take those end-of-day chat message transcripts and extract something actionable: structured quote data, complete with timestamps, context, and source messages. No more lost quotes. No more lost intent. Just a clean view of what happened, when and enabling you to act on it.
This is a textbook example of our Orchestrate pillar in motion.
Capture the raw, unstructured chat.
Orchestrate it into structured, contextualised output.
Deliver it wherever it’s needed: Quote Hub, OMS, Data-as-a-Service or Excel.
How It Works:
The flow is simple and utilises the full power of ipushpull's capital markets expertise:
| Stage | Purpose | Output |
|---|---|---|
| Ingest | Securely receive daily transcript files | Raw chat file |
| Identify & Link | Detect quote actions, normalise speakers, and group updates | Message-level rows |
| Extract & Enrich | Pull instrument, price, size, side and owner. Apply reference data & metadata to enrich the data | Normalised quote events |
| Publish | Push to blotter, API, warehouse, Excel | Live and historical feed |
Some of the key capabilities that make this work:
-
Handles conversational quotes. Conversations aren’t clean. This keeps multiple, mixed quote threads sorted and intact.
-
Context-aware enrichment. When someone says “same as before”, the system remembers what that means.
-
Nested blotter view. See every add, update, or cancel as expandable rows with full traceability.
-
Validated data. This is a ready-made data product for downstream analytics, partners, or internal teams.
Why It Matters:
This isn’t just about cleaning up chat. It’s about pulling commercial value out of previously wasted data.
| Outcome | Benefit |
|---|---|
| New Data Opportunities | Create richer quote and IOI feeds for clients |
| Efficiency at the Desk | Start the day with a pre-populated blotter of client interests |
| Knowledge Retention | Keep insight institutional, not desk-bound or siloed |
| Analytics and Reporting | Surface customer trends, behaviours, and position changes |
| Historical Intelligence | Build years of machine-readable quote history, ready for flow analysis |
| Audit Trail | Store the original chat line alongside every derived quote for full transparency |
The platform is already running and ready to demo.
We’re treating this as a foundation for broader quote capture and order orchestration tools. You’re sitting on a mountain of unstructured chat; this is a simple way to turn it into value.
Try It Out
-
Share a transcript.
-
We’ll process it and deliver a blotter and flat file.
-
You tell us what’s right, what’s missing, and we improve.
-
If it works, we agree terms and start sending a daily feed.
This is one of several use cases under ipushpull’s Orchestrate pillar. Others, like trade capture, booking and quote enrichment, follow the same model, structured, auditable, context-rich data flowing into the systems and people that need it.
That’s how you build real automation in capital markets. And it starts with listening to the data you already have. Got more questions? Why not contact us to discuss further.
