Feature · RPA (Robotic Process Automation)

RPA (robotic process automation) that uses APIs instead of UI scraping.

The repetitive jobs classic RPA bots cover (lead triage, data entry, document extraction, reconciliation, scheduled reporting) run native inside Strkr Flows. 10 to 100 times faster than UI bots, no per-bot license, one audit log, included.

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What RPA actually is

The useful shape, delivered without screen scraping.

RPA (robotic process automation) is software that automates repetitive tasks by mimicking human interactions with computer systems. The classic approach is screen-scraping: software bots that open applications, click buttons, read fields, and type data between systems. The approach was designed for legacy systems that lacked modern APIs. For modern SaaS systems with APIs, native API-based automation delivers the same jobs with better economics. Strkr implements the useful RPA shape (automate the repetitive) through native integrations and Flows runtime rather than through bots that mimic human clicks.

Classic RPA

Screen-scraping bots for legacy systems.

Classic RPA bots open a target application's UI, read values from on-screen fields, and type values into other on-screen fields. The approach handles legacy systems (mainframes, old desktop apps, government portals) that have no API. The bot is slow (2-5 seconds per interaction) and breaks when the UI changes.

Modern RPA

Native API automation for API-enabled systems.

For modern SaaS systems with APIs, native automation (10-100 milliseconds per interaction) replaces screen scraping. The automation is faster, more reliable, and does not require specialist RPA developers. For revenue-operations work on modern SaaS, this is the better tool.

Hybrid approach

Native for modern, RPA for legacy.

Most mid-market revenue orgs run some modern SaaS and some legacy systems. The right approach is hybrid: native automation (Strkr Flows) for the modern lattice, classic RPA for the legacy edge, with the two coordinated via webhooks and API callbacks.

AI augmentation

Intelligent automation, native rather than add-on.

Classic RPA vendors sell AI as a separate "intelligent automation" tier (document OCR, email classification, entity extraction, draft generation). Strkr AI is a step inside any Flow by default. The AI layer that costs extra on classic RPA is included.

Governance

One permission model, one audit log.

Classic RPA runs bots as dedicated service accounts with broad access, creating a shadow privileged user compliance has to govern separately. Strkr Flows runs as a user and respects that user's permissions. Automated writes land in the main audit log along with every other change.

Included

No per-bot license.

Classic RPA licenses per bot (attended, unattended, developer, orchestrator) plus infrastructure (bot-execution servers, Windows licenses, monitoring). Strkr Flows is included with the suite at predictable per-seat pricing with unlimited runs.

The specific RPA jobs

The repetitive tasks mid-market revenue teams automate.

RPA covers hundreds of theoretical use cases. The specific jobs that produce measurable ROI for a mid-market revenue team are a short list. Strkr delivers them through native Flows rather than through screen-scraping bots.

Lead triage

Form submits enriched, scored, routed, drafted.

The classic RPA lead-triage bot reads the latest form submits, enriches each from a vendor, grades fit and intent, assigns to the right rep, drafts a first-touch reply. Strkr's Flow does the same job in under 30 seconds using native APIs: no bot that mimics an SDR's mouse clicks across six tabs.

Data entry

Field updates from external sources.

The RPA data-entry job pulls values from one system and writes them to another. Strkr's Flow queries the source's API, pulls the data in bulk, writes it to the matching records. The 20-minute bot run against 100 records becomes 10 seconds.

Document extraction

OCR and field extraction, native AI step.

The RPA document-processing bot reads PDFs (invoices, contracts, order forms), extracts fields, writes them to the system of record. Strkr AI handles the extraction as a native step inside Flows. No separate OCR vendor subscription, no bot that opens Adobe Reader.

Reconciliation

Match records across systems.

The RPA reconciliation job pulls records from two systems, matches them, flags discrepancies. Strkr's Flow queries both via API, performs the match, writes discrepancies to a task list. Finance's month-end reconciliation that takes two days takes under an hour.

Report generation

Scheduled aggregation and distribution.

The RPA reporting job runs saved reports, exports them to Excel, formats, emails to recipients. Strkr's dashboard surface delivers reports natively via scheduled Flows (email, Slack, PDF). The RPA bot for scheduled reports is replaced by a product surface.

Routine notifications

Status checks and alerts across systems.

The RPA notification bot checks a system for a status change, formats a notification, sends it. Strkr's Flow listens for the event natively (webhook or API poll), formats the notification, sends via native Slack / email / SMS. One Flow replaces three bots.

How to think about the switch

When to replace an RPA bot with a native Flow.

Teams running classic RPA deployments typically do not swap everything out at once. The useful question is which bots to migrate first and which to leave on RPA. Strkr's guidance: migrate the bots where native APIs exist, keep the bots where the target system has no API, and run the two layers coordinated via webhooks.

API availability

If the target has an API, native wins.

Every modern SaaS system (CRM, marketing automation, messaging, project tracker, finance) has an API. For any bot that currently automates one of these via UI scraping, a native Flow is faster, more reliable, and cheaper. Migrate first.

Legacy edge cases

If no API, RPA stays.

Mainframes, government portals, old desktop apps: no API exists. For these, keep the RPA bot. Strkr's Flow can trigger the RPA bot via outbound webhook and receive the result via return webhook. The two systems coexist cleanly.

Partial migration

Replace the UI step with the API step.

Some bots have mixed shape: part legacy (no API) and part modern (API available). Rebuild the modern part as a native Flow, keep the legacy part on RPA, coordinate via webhook. The modern lattice grows; the RPA footprint shrinks.

AI augmentation

Add intelligence where the bot was blind.

Classic RPA bots are rule-based: if-this-then-that against fixed field positions. Native Flows can insert Strkr AI as a step for the cases where intelligence matters (classify intent, extract from unstructured text, draft a response). Capabilities the RPA bot could not deliver without an AI-tier upsell are included.

Governance consolidation

One audit log for both automation layers.

When the RPA bot writes to Strkr via the API, the write lands in Strkr's main audit log. Compliance review happens on one surface rather than reconciling across the RPA bot-execution log and the system audit log. The governance program simplifies.

License recovery

Shrink the RPA footprint, shrink the bill.

Per-bot RPA licenses are the biggest line item in a classic deployment. As bots migrate to native Flows, the RPA license count drops. Over a quarter or two the RPA bill typically shrinks by 60-80 percent while automation coverage increases.

The AI layer that comes included

Intelligent automation without an add-on module.

Classic RPA vendors sell AI as a separate tier: Intelligent Document Processing, Cognitive Automation, Communications Mining, Document Understanding. Each is a license line and a specialist-training requirement. Strkr AI is a step inside any Flow by default. The AI layer that costs five figures as an add-on in the classic RPA stack is included.

Document OCR

PDF to structured fields.

Drop a PDF into a Flow. Strkr AI extracts fields (invoice number, amount, due date, line items) to structured output. Next step writes to the record. The classic RPA "Intelligent Document Processing" add-on is a native AI step.

Email classification

Inbound replies routed by intent.

Inbound email arrives. Strkr AI classifies the intent (interested, not interested, OOO, question, unsubscribe). Flow routes based on classification. The classic RPA "Communications Mining" module is a native step.

Entity extraction

Named entities from unstructured text.

A call transcript, chat log, long email thread. Strkr AI extracts named entities (people, companies, amounts, dates, products). Flow writes them to the deal or contact. The classic RPA "Entity Recognition" module is included.

Classification

Categorize records at scale.

A batch of leads needs qualification. Strkr AI reads each one, classifies against the ICP, returns a score. Flow routes by classification. The classic RPA "ML Classification" module is included.

Summarization

Long content into short summaries.

A long thread, long document, long call transcript. Strkr AI produces a two-sentence summary. Flow posts it as a note on the record. The classic RPA "Cognitive Summarization" module is included.

Draft generation

AI-written outputs inside the Flow.

Draft an email reply, draft a follow-up SMS, draft a proposal section. Strkr AI produces the draft inside the Flow. The RPA "Generative Automation" add-on module is a native action.

Governance and compliance

The production-grade surfaces regulated teams need.

RPA governance in regulated industries (banking, insurance, healthcare) is a specialized program: bot-review boards, change-control, audit-log reconciliation, specialist compliance officers. Strkr's governance ships as product surfaces so the automation layer is auditable without a separate specialist program.

Permission inheritance

Flows run as a user.

A Flow runs as its owner by default. Actions and AI steps respect the owner's permissions. Admins can elevate specific Flows to a service account with the elevation visible on the Flow's detail page. No shadow god-mode user.

Data classification

Sensitive fields treated differently.

Fields marked sensitive (SSNs, bank accounts, health identifiers) are stripped from AI prompts and masked in log entries. Automation that would write a sensitive value to an external integration requires explicit admin approval.

Approval queue

High-governance tenants gate Flow changes.

Regulated-space tenants require that new Flows or AI steps are reviewed and approved before going live. The approval queue surfaces diffs; approvers sign off with comments. SOC 2 and ISO change-control satisfied on one surface.

Audit log

Every automated action in the main log.

Flow runs, AI calls, integration writes, all land in the main audit log. Compliance review happens on one surface rather than reconciling across a bot-execution log and the system audit log.

Rate limits

Prevent runaway loops.

Flows cannot recurse past a tenant-configurable depth. AI steps have per-user daily caps. A misconfigured Flow that would fire a thousand times hits the limit, pauses, surfaces to admin.

Export audit

Every automated action, exportable.

Audit log exportable to CSV or Parquet on demand or on a schedule. SOC 2 Type II and ISO 27001 auditors have the full automation history without a special export program.

Compared to the alternatives

Native vs classic RPA vendors.

The RPA category is populated by specialized vendors optimized for screen-scraping legacy systems. For revenue-operations work on modern SaaS, native automation is the better tool on every axis. Strkr's Flows runtime captures the useful shape of RPA without the license, infrastructure, specialist-labor, and maintenance tax.

UiPath

Enterprise leader, per-bot licensed.

UiPath is the enterprise RPA standard. Priced per bot plus infrastructure. Right tool for API-less legacy systems; overkill for API-enabled modern SaaS.

Automation Anywhere

Cloud-native RPA, similar economics.

Automation Anywhere competes head-to-head with UiPath. Similar price shape, similar specialist-developer requirement, similar fit for legacy systems.

Blue Prism

Compliance-heavy, regulated-industry fit.

Blue Prism is favored by banks and healthcare for the governance surfaces. Strict change-control, enterprise price. Overkill for revenue-ops teams where native automation works.

Microsoft Power Automate

Approachable, Microsoft-ecosystem fit.

Power Automate includes both API-based automation and RPA (Power Automate Desktop). Approachable for Microsoft stacks; non-Microsoft fit is weaker.

Workato and Tray.io

iPaaS adjacent to RPA.

Workato and Tray.io are integration platforms (iPaaS) that overlap with RPA for API-based automation. Priced per workflow or per operation. Strkr's native Flows removes the external platform layer entirely for revenue-ops use cases.

Strkr Flows + AI

Native automation, included, modern-SaaS focused.

Flows runtime, Strkr AI steps, every native integration, full audit log, dry-run mode, version history, dead-letter queue, all shipping on Pro and above. No per-bot license, no bot-execution infrastructure, no specialist-developer requirement.

What RPA migration actually looks like

Six moves teams make on the way off UiPath, Automation Anywhere, or Power Automate.

We have watched teams move about 40 RPA deployments to Strkr Flows across the last two years. The projects share a specific shape. Not glamorous, but predictable enough to describe honestly.

The audit first

A full bot inventory tells you how big the project is.

The first week of any RPA migration is building the honest inventory: which bots fire, how often, what they actually do, and which depend on which. A 220-rep logistics group we migrated had 47 UiPath bots on the list. The audit found 12 that had not fired in six months, 8 that duplicated newer bots, and 3 that touched systems that had been retired. The real migration scope was 24 bots, not 47.

API-first replacement

Rebuild as native Flows where APIs exist.

For bots that touch modern SaaS, the rebuild happens in Strkr Flows using native APIs. The flow typically runs 10 to 100 times faster than the UI bot it replaced because it is calling an endpoint instead of scraping a screen. A manufacturing distributor we worked with replaced 14 UiPath bots with 11 Strkr Flows in six weeks and reports zero bot-breakage incidents since.

Keep the legacy edge

Some bots stay because the target system has no API.

The honest conversation includes which bots cannot be rebuilt as native automation. Legacy government portals, old desktop apps, specific vendor UIs with no public API all stay on classic RPA for now. The project goal is not zero RPA; it is zero unnecessary RPA. The remaining 15 to 30 percent of bots that touch legacy systems coexist with Strkr via webhook callbacks.

Document extraction consolidates

The IDP line item disappears into native AI steps.

Classic RPA deployments usually layer a separate Intelligent Document Processing SKU for OCR and extraction. On Strkr, document extraction runs as an AI step inside any Flow with no separate license. A professional services firm we worked with retired a $48K per year Automation Anywhere IQ Bot license when they migrated the document workflows into Strkr Flows.

Governance consolidates

One audit log replaces three.

Classic RPA deployments ship their own bot execution logs, their own permission model, and often their own compliance tooling. Migration collapses this into one audit log and one permission model for the modern automation surface. Compliance review becomes a single export rather than reconciling three logs. For teams running SOX attestation, this is a measurable time save per quarter.

The license line shrinks

Per-bot pricing becomes included.

The RPA license line typically drops by 60 to 80 percent through the migration. A 50-rep SaaS team we worked with was paying $120K per year on UiPath bots plus bot-execution infrastructure. Post-migration they kept 4 UiPath bots on legacy systems at $12K per year and ran the rest native. The savings funded two more RevOps hires inside the same budget.

Flows ships on Pro. Strkr AI ships on Pro. The RPA jobs most revenue teams need are included.

Native automation across the revenue stack with no per-bot license, no bot-execution infrastructure, no specialist-developer requirement.

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Common questions

What buyers ask about this feature.

What is RPA (robotic process automation)?

RPA is software that automates repetitive tasks by mimicking human interactions with computer systems. The classic approach deploys software bots that open applications, click buttons, read fields, and type data between systems. The approach was designed for legacy systems that lacked modern APIs (mainframes, government portals, old desktop apps). For modern SaaS systems with APIs, native API-based automation delivers the same jobs faster (10-100x), more reliably, and without specialist developers. Strkr implements the useful shape of RPA through native integrations and the Flows runtime rather than through screen-scraping bots.

What are examples of RPA automation?

Common examples: lead triage (read form submits, enrich, score, route, draft reply), data entry (pull values from one system, write to another), document extraction (read PDFs, extract fields, write to records), reconciliation (match records across systems, flag discrepancies), report generation (run reports, format, email to recipients), routine notifications (check status changes, send alerts). Each of these is a classic RPA use case. In Strkr they ship as native Flows that use APIs rather than UI scraping. The result is faster execution, better reliability, and no per-bot licensing.

How is RPA different from workflow automation?

RPA was originally defined by its approach: screen-scraping bots that mimic human UI interactions, built for legacy systems without APIs. Workflow automation is a broader category: any software that executes a sequence of steps based on triggers and conditions. The two categories have converged as RPA vendors added API-based capabilities and workflow automation tools added screen-scraping options. The practical distinction is: use screen-scraping when the target has no API; use API-based workflow automation when the target has an API. For revenue-operations work on modern SaaS, API-based automation covers roughly 90 percent of use cases.

When is RPA still worth deploying?

Three cases where RPA remains the right tool. First, no-API systems: legacy mainframes, government portals, old desktop apps, vendor UIs with no public API. Second, migration bridging: during a move from a legacy system to a modern SaaS, RPA can keep the legacy running while the modern integrations stabilize. Third, extreme UI-only workflows: if the entire "process" being automated is a human clicking through screens in a specific order with no system changes, RPA fits the shape. For revenue-operations work on modern SaaS, native automation is the better tool and should be the first choice.

Can Strkr replace an existing RPA deployment?

For the revenue-operations portion, yes. Teams running classic RPA (UiPath, Automation Anywhere, Blue Prism, Power Automate) typically migrate bot-by-bot to native Flows where modern APIs exist. The RPA footprint shrinks to just the legacy-edge cases. Strkr's native integrations include outbound webhooks to call RPA orchestrators and inbound webhooks to accept callback results, so the two systems coexist cleanly during migration. Over a quarter or two the RPA license count drops by 60-80 percent while automation coverage increases through added AI capabilities and native cross-module Flows.

Does Strkr include document OCR?

Yes, as a native Strkr AI step inside any Flow. Drop a PDF into a Flow and the AI extracts the fields (invoice number, amount, due date, line items, contract terms) to structured output. The next step writes the extracted fields to the record (contact, deal, invoice, order). The capability that classic RPA vendors sell as "Intelligent Document Processing" with a separate license is included on Pro with no add-on SKU. Teams processing high volumes of invoices, contracts, or forms typically see this as the most valuable AI step in their Flow library.

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