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"Capture" is Where It All Starts
In a world of PDFs, Excel files, REST APIs, chat messages, voice transcripts, and bespoke file formats, financial institutions are inundated with fragmented, inconsistent data. Most firms spend far too much time wrangling inputs into something usable. At ipushpull, we believe the Capture layer is the foundation for scalable, intelligent workflows.
Capture is the first of our three core product pillars, Capture, Orchestrate, Deliver, that enable financial firms to turn chaotic, multichannel data into structured, compliant workflows.
The Real Challenge with Data Capture
Across desks, divisions, and regions, incoming data arrives in wildly different formats:
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PDFs with embedded tables
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Excel sheets
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Unstructured chat threads
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Semi-structured voice-to-text summaries
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Flat files from external partners
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REST endpoints that change without notice
These aren’t just annoying. They’re operational bottlenecks, risk amplifiers, and blockers to automation. Our job is to make them disappear.
Any Endpoint, One Stream
Our Capture Layer is designed to ingest anything from anywhere and instantly structure it in a consistent, queryable format. For example, ipushpull’s REST-as-a-Service (RaaS) provides a single, configurable gateway for every REST endpoint your organisation needs, third-party vendors, cloud platforms, or downstream clients. You write connectivity to one ipushpull REST interface; every additional source or destination is added with configuration only, eliminating repeat development and accelerating time-to-market. We offer:
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Inbound aggregation – Pull data from any REST service (public, private, on-prem, cloud) and receive it through a single, stable ipushpull endpoint.
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Outbound routing – Push data from your application to one or many REST targets with dynamic routing rules.
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Protocol mediation – Convert SOAP, GraphQL or WebSocket sources to REST (and vice-versa) when required.
Designed with Speed and Flexibility at the Core
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A top-tier interdealer broker requested five new capture feeds from Excel sheets. We implemented their workflow in under 48 hours.
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An exchange needed live ingestion of security notices in PDF format. We did the analysis, wrote the configuration and demo'd back to them the next day.
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A global bank needed to connect chat-based client requests into a downstream STP engine. This was implemented within a week.
Key Benefits
We're not a tool. We're an integration layer built for messy real-world data.
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Benefit |
Impact |
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Connect once, configure many |
Add or swap endpoints in minutes without code changes. |
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Faster onboarding |
New clients or vendors join via declarative configs. |
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Reduced tech debt |
Centralises integrations and transformations, cutting bespoke code. |
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Consistent data quality |
Enrichment & validation ensure downstream systems receive complete, standardised payloads. |
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Bidirectional flexibility |
Same engine handles inbound and outbound flows, including fan-out to multiple services. |
Future-Proofing for AI and Agents
This is more than operational convenience. As firms begin exploring LLMS, autonomous agents, and chat-driven workflows, the quality and traceability of the underlying data becomes mission-critical.
If you're not capturing and normalising that data today, you're not preparing your enterprise for agent-based workflows tomorrow.
Coming Next: In our next blog, we’ll explore how orchestrated data flows power true automation, not just scripts or macros, but intelligent, governed workflows across the enterprise. Until then, if you’re wrestling with data ingestion headaches or planning for AI-readiness, let’s talk.
