Enterprise work, especially in fintech involves a ton of systems and workflows. A wealth manager might receive a client request, check the CRM, open a portfolio system, validate data in Excel, copy an identifier into a legacy app, update a ticket, send an email, and then notify another team.
Both RPA and interop platforms try to reduce that friction, but in different ways.
RPA usually starts from the task: “A person performs these steps repeatedly. Can a bot perform them instead?” It can automate repetitive, rule-based work such as data entry, file movement, transaction processing, and system integration by mimicking human actions in digital systems.
Interop platforms like io.Connect usually start from the application estate: “Several applications are already part of a user workflow. Can they behave more like parts of one system?” A desktop or browser interop platform allows apps to be combined at the UI level so users can access the right data and functionality at the right time, reduce copy-paste, and connect legacy, third-party, modern web, and native apps so they can interact in real time.
RPA workflow example
An accounts payable team receives vendor invoices by email - here’s an RPA workflow:
- The bot monitors a shared mailbox for new invoice emails.
- When an invoice arrives, it downloads the PDF attachment.
- It extracts basic fields: vendor name, invoice number, date, amount, and purchase order number.
- It opens the ERP system.
- It enters the extracted data into the invoice form.
- It attaches the original PDF.
- It submits the record.
This is a good RPA example because the task is repetitive, rule-based, and execution-oriented. It saves manual work on behalf of the user, but needs maintenance e.g., when the ERP UX or invoice format changes.
io.Connect workflow example
Here a financial advisor is handling a client issue. The work is not a simple sequence that can run unattended.
An io.Connect workflow can look like this:
- The client calls the wealth manager on Teams.
- The client identity is loaded in io.Connect as context.
- io.Connect opens or restores a saved "Client Call" Workspace Layout (more about workspaces and layouts here - Interop User Journeys: Fixed Workflows or Power User Freedom ) passing the client identity as the initial Workspace context.
- The Workspace loads the relevant apps in one coordinated view: CRM profile, household accounts, portfolio holdings, recent transactions, performance chart, risk analytics, research/news, advisor notes, suitability checklist, Excel, and Outlook.
a. The selected client becomes the active shared context.
b. The CRM shows the client profile and relationship history.
c. The portfolio app loads the client’s accounts, holdings, cash positions, and recent activity.
d. The risk app shows current exposure, concentration, volatility, and suitability warnings.
e. The research app shows news and research related to the client’s largest holdings or watchlist. - The client asks, “What happens if we reduce exposure to this sector?” The advisor makes a selection and the rest of the Workspace narrows to it: risk, performance, transactions, etc.
- The advisor changes a proposed allocation in the model portfolio app.
- The risk app recalculates the impact by exposing a risk calculation as an Interop Method.
- The advisor clicks a Prepare Follow-Up button that raises an Intent. io.Connect activates the right app for preparing a proposal, meeting note, or follow-up email.
- Outlook opens with the client context, meeting subject, and relevant portfolio notes already available.
- After the call, the advisor saves the Workspace state, including app arrangement and relevant context, so the review can be resumed later.
The goal is not to replace the user, but to coordinate applications around the user. It’s an infrastructure that gives applications shared ways to exchange context, expose capabilities, launch workflows, and present themselves as part of one desktop experience.
Side-by-side comparison
A simple “RPA vs interop” framing can be misleading because the two operate at different layers.
| Layer | RPA | Interop platform |
|---|---|---|
| Primary abstraction | Simple task sequence | Complex application collaboration |
| Main actor | Bot | User plus dozens of connected apps |
| Integration style | UI automation, selectors, scripts, connectors | APIs, contexts, methods, streams, app definitions, Workspaces and Layouts |
| Best workflow type | Repetitive, rule-based, often back-office | Real-time, context-heavy, human-in-the-loop |
| Long-term maintenance | Fragile if UI/process changes | Requires integration design |
| User experience impact | Reduces simple repetitive work | Improves live multi-app workflows |
| Governance focus | Bot lifecycle, credentials, exceptions, audit | App definitions, permissions, contracts, context design, platform configuration |
The difference is not “automation vs no automation.” Interop also enables automation. The difference is what gets automated. Interop fits especially well when:
- The user still needs to decide, review, compare, approve, or investigate.
- Several apps need to stay aligned around the same client, instrument, ticket, order, case, or workflow.
- The organization wants reusable desktop capabilities rather than one-off scripts.
- The workflow is interactive and real-time.
- Visual organization matters, not just backend execution.
- Apps need to expose business functions to each other.
Is interop a replacement for RPA?
RPA and Interop solve different problems.
A good automation strategy may use both: interop to make the live desktop workflow coherent, and RPA to execute repetitive downstream work when there is no need for human judgment.