Feature · RPA Integration

RPA integration that keeps the audit trail unbroken across both sides.

Teams running existing RPA estates need the bot output to land cleanly on the CRM, and the CRM to be able to queue work back to the bot for legacy-system actions. Strkr is a modern CRM-native platform, not an RPA tool, but it integrates with the major RPA platforms (UiPath, Blue Prism, Automation Anywhere, Microsoft Power Automate, Robocorp) through first-class webhooks and APIs. Every write carries provenance (bot name, source system, timestamp) and every integration is in the single append-only audit log the rest of the platform uses. The two layers coexist with one audit trail.

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What the integration does

The six ways bots and Strkr exchange work.

The integration surface between an RPA estate and a modern CRM has six patterns: bot writes to CRM, CRM queues to bot, bot reads CRM context, bot updates on long-running processes, bot error handling in CRM, and audit reconciliation across both sides. Strkr ships each pattern as a first-class capability rather than a one-off script.

Bot writes to CRM

Bot output lands on the record.

A bot pulling data from a legacy system writes to the Strkr account, contact, deal, or custom-object record via webhook. The write carries the actor (bot name), the source system, and the timestamp. The audit log on the receiving record shows exactly where each value came from, with reversible history.

CRM queues to bot

Strkr fires work to the bot runtime.

A Strkr flow fires a webhook to the bot runtime (UiPath Orchestrator, Blue Prism Hub, Automation Anywhere Control Room, Power Automate flow) with the full record context. The bot picks up the request, acts on the legacy system, and writes a status back. The audit log records the queue and the completion.

Bot reads context

Live record context for the bot run.

A bot that needs account tier, contact title, or deal stage before it acts queries the Strkr API for live record context at run time. The response is current (not a nightly extract) and includes the fields the bot needs. The call is logged on the record so the audit shows what data the bot read.

Long-running updates

Status updates on multi-step bot work.

For long-running bot processes (document processing with human review, multi-system orchestration) the bot posts intermediate status updates to Strkr. The owner reads the current state on the record rather than opening the bot runtime. The handoff pattern keeps the CRM as the source of truth.

Error handoff

Bot errors route to the right owner.

When a bot fails (UI change, upstream data problem, exception path hit), the error posts to Strkr as a task with the context, the attempted action, and the suggested resolution. The owner handles the exception in the CRM; the bot runtime does not need its own ticketing UI.

Audit reconciliation

One audit log across both sides.

Every bot action and every Strkr action lands in the same append-only audit log, filterable by actor, source, record, and date. A regulatory question that touches both bot and CRM steps gets one answer, not a reconciliation across two systems.

Platforms supported

The six RPA platforms with first-class integration.

Strkr ships first-class integration patterns for the six RPA platforms most enterprises run in 2026. The patterns are configuration, not custom development: an admin sets the credentials, configures the webhook endpoint, and the two platforms exchange work with full audit. Custom RPA platforms are supported through the generic webhook interface.

UiPath

Orchestrator queues, Studio triggers.

Strkr integrates with UiPath Orchestrator via webhook: flows post to Orchestrator queues with the record context, bot results post back to Strkr with provenance. UiPath Studio triggers can call the Strkr API directly for mid-process reads. Credentials are KMS-encrypted in Strkr's integration vault.

Blue Prism

Hub webhook, work queue bridge.

Blue Prism Hub webhook integration routes work from Strkr to Blue Prism control rooms. Work queue items write back as record updates. The ROM governance surface in Blue Prism reads Strkr activity cleanly for cross-system audit.

Automation Anywhere

Control Room API, bot callback.

Automation Anywhere Control Room API integration lets Strkr flows trigger bot runs with context and receive callbacks on completion or error. The A2019 platform is the supported baseline; V11 integration is supported but deprecated upstream.

Microsoft Power Automate

HTTP action, Dataverse bridge.

Power Automate flows (cloud and desktop) exchange with Strkr through the HTTP action for direct webhook calls, and through a Dataverse bridge for Microsoft 365-heavy teams. The ops lead can keep Power Automate for the Microsoft 365 processes and run Strkr-native flows for the CRM processes.

Robocorp

Python RPA with developer tooling.

Robocorp (open-source RPA Framework) integrates through standard webhooks and the Strkr Python SDK. Teams with Python engineering resources benefit from the developer-grade tooling; the audit trail stays unified across the open-source bot layer and Strkr.

Custom and legacy

Generic webhook interface.

Any RPA runtime that can call an HTTP endpoint integrates through Strkr's generic webhook interface. The admin configures the inbound shape and the credentials; the audit trail picks up the same way as the first-class integrations. Legacy in-house automation layers can plug in cleanly.

What provenance tracking adds

The six fields on every bot-written value.

The capability that separates a working RPA integration from a drift-prone one is provenance tracking. Every write a bot makes to Strkr carries six specific fields of context, which the audit panel on the record surfaces in one click. The provenance makes bot-written data defensible and reviewable.

Bot name

The bot that wrote the value.

The bot name (not just "RPA") is stamped on the write. The ops lead reading the audit knows which specific bot wrote the field, which matters when multiple bots run against the same record. A pattern of conflicting writes across bots surfaces immediately.

Source system

Which upstream the bot read from.

The source system (CIS, mainframe, vendor portal) that the bot pulled the value from is on the write. If the mainframe is wrong, the ops lead can trace which fields got populated from it and run a targeted correction. The source dimension of the audit matters as much as the actor.

Timestamp

When the bot wrote the value.

An exact timestamp is on every write. The audit panel shows the full history of a field over time with each write's source. A board asking "when did this account tier change" gets the exact answer in one click, with the bot that wrote the change named.

Confidence

How sure was the bot.

For OCR, extraction, and matching operations the bot writes a confidence score alongside the value. The ops lead can gate high-impact writes on confidence (route low-confidence to review) and the audit shows which values were auto-accepted vs. reviewed.

Reversibility

Prior value is one click to restore.

Every bot-written value has the prior value in the audit history. A bad batch run can be reverted one record or in bulk without a backup restore. The revert itself is logged append-only, so the audit shows both the bad write and the correction.

Linked bot run

Jump to the bot runtime log.

The audit entry links to the bot run in the RPA runtime (UiPath Orchestrator log, Power Automate run detail). A compliance reviewer can see the Strkr write and jump to the bot runtime log for the full execution trace without reconstructing the chain by hand.

How to design the integration cleanly

The six patterns a mature deployment uses.

A good RPA-plus-CRM integration follows six patterns. Each is a design choice that pays back on reliability and audit. A deployment that skips the patterns ends up with silent write collisions, orphan bot runs, and audit gaps that surface at the worst moment. The six cards describe each pattern.

Clear ownership

One side owns each field.

Each field on each record has a clear owner (bot or CRM-native flow). Two sources writing the same field with different rules creates drift. The ops lead documents ownership and the audit log catches any violations immediately.

Idempotent writes

Replaying a bot write is safe.

Bot writes are designed to be idempotent (the same write applied twice has the same result). Retries on transient failures do not create duplicates. The pattern is standard in good API design and worth enforcing in bot development too.

Explicit error paths

Every failure routes to a human.

Every bot failure routes to a human owner in Strkr with the context and the attempted action. Silent failures (bot errors, moves to a dead-letter queue, nobody notices) are the leading cause of audit gaps. Make every failure a task.

Rate limits respected

Bots pace to CRM API limits.

Bot runs that read or write Strkr respect the API rate limits with retry-and-backoff. A bot that bursts past the limit sees a 429 and backs off cleanly. The pattern keeps the integration healthy under peak volume.

Context payloads

Rich payloads, not just an id.

The webhook from Strkr to the bot includes rich context (full account, deal, and relevant history), not just an id. The bot does not need to re-query for every field. The pattern reduces API load and makes bot development cleaner.

Versioned contracts

Webhook shapes are versioned.

The webhook payload shape is versioned (v1, v2). A Strkr platform change that adds fields does not break the bot that expected the v1 shape. The ops lead opts into the new version when the bot is updated to consume it. The pattern avoids disruptive forced upgrades.

When to retire a bot

The six signals that a bot should move to native.

Not every bot stays forever. Six signals indicate a bot is ready to retire in favor of a Strkr-native flow or a direct API integration. A healthy RPA-plus-CRM portfolio retires the right bots on cadence so the estate shrinks as the underlying stack modernizes. The six cards name the signals.

Target vendor ships API

The reason for the bot went away.

A vendor that shipped a public API during the bot's life has removed the architectural reason for the bot. The direct API call is cheaper, more durable, and better audited. Retire the bot, build the API integration natively, keep the audit continuity through the transition.

Native capability lands

Strkr shipped the feature.

When Strkr ships a native capability that replaces a bot's role (new routing rule, document generation improvement, enrichment provider), the bot can retire. The retirement writes off the maintenance tail and consolidates the audit on the native side.

Maintenance exceeds build

The ongoing cost no longer pays back.

A bot whose annual maintenance cost exceeds its original build cost is no longer paying back. The ops lead should either migrate to native, upgrade the integration path, or retire the process entirely. The math is often not reviewed; schedule the review annually.

Low utilization

Bot runs rarely but still breaks.

A bot that runs once a month but still breaks when the vendor UI changes is a bad trade. The volume does not justify the maintenance; the audit requirement might still be real. Retire the bot and run the process as a scheduled flow with manual steps.

Platform migration

Underlying system is being replaced.

A bot against a legacy system that is being replaced has a known end date. The retirement should be in the migration plan from day one. The audit log captures the final bot runs and transitions to the native capability.

Risk profile shift

The regulator changed the audit bar.

A regulator that raised the audit bar on a process may make a bot approach no longer defensible without additional controls. If the native approach has stronger built-in audit, retire the bot in favor of native. The compliance posture improves at the same cost or less.

Keep the RPA estate for what it does well; integrate with Strkr for everything downstream.

Webhook in, webhook out, provenance on every write, one audit log across both sides. First-class integration with UiPath, Blue Prism, Automation Anywhere, Power Automate, and Robocorp.

See the integration patterns Explore RevOps Automation
Common questions

What buyers ask about this feature.

Does Strkr replace RPA tools?

For the common sales-ops and RevOps automations (lead routing, pipeline hygiene, forecast cadence, enrichment, dedupe, document generation, handoff) Strkr's native workflows replace the bots that typically covered those use cases. For legitimate bot cases (mainframe or no-API vendor, regulatory portals, attended-mode desktop tasks) Strkr does not replace the RPA tool, it integrates with it. Teams typically run both: Strkr for the modern CRM-native side, RPA for the legacy-system side, with webhook integration keeping the audit log unified.

Which RPA platforms does Strkr integrate with?

First-class integration patterns for UiPath (Orchestrator queues and Studio triggers), Blue Prism (Hub webhook and work queue bridge), Automation Anywhere (Control Room API with bot callbacks), Microsoft Power Automate (HTTP action and Dataverse bridge for Microsoft 365-heavy teams), and Robocorp (standard webhooks plus Strkr Python SDK). Any other RPA runtime integrates through the generic webhook interface with the same audit discipline.

How does provenance tracking work on bot-written data?

Every bot write to Strkr carries six fields of provenance: bot name, source system, timestamp, confidence score (where relevant), reversibility hooks, and a link back to the bot run in the RPA runtime. The audit panel on the receiving record surfaces all six in one click. A compliance reviewer can see the Strkr write and jump to the bot runtime log for the full execution trace without reconstructing the chain manually.

What about audit for regulated industries?

Every bot action and every Strkr action lands in the same append-only audit log, filterable by actor, source, record, and date range. For a regulatory question that touches both bot and CRM steps the auditor gets one answer rather than reconciliation across two systems. Retention is tenant-configurable to match the regulatory requirement. For HIPAA-covered workflows Strkr offers a BAA; SOC 2 Type II is in progress for 2026-Q4.

Can bots read live CRM context at run time?

Yes. A bot that needs account tier, contact title, or deal stage before it acts queries the Strkr API for live record context at run time. The response reflects the current state (not a nightly extract) and includes the fields the bot was configured to read. The API call is logged on the record so the audit shows what data the bot read. Credentials are KMS-encrypted in Strkr's integration vault.

When should a bot retire in favor of native?

Six signals indicate retirement: the target vendor shipped an API that removes the architectural reason for the bot; Strkr shipped a native capability that covers the bot's role; the annual maintenance cost exceeds the original build cost; utilization is low but the bot still breaks on UI changes; the underlying system is being replaced; or a regulator raised the audit bar beyond what the bot can defensibly meet. A healthy RPA-plus-CRM portfolio reviews these signals annually and retires the right bots on cadence.

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