Feature · Robotic Automation

Robotic automation that runs inside the CRM, not next to it in a bot farm.

The bots that revenue teams actually need are the ones that live on the record. Strkr runs lead-routing bots, deal-updating bots, renewal-prep bots, support-triage bots, and reporting bots as native workflow nodes with observability, retries, and audit logging. No separate RPA license, no citizen-developer sandbox, no UI-scraping scripts breaking the week someone pushes a browser update.

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What robotic automation means for a revenue team

The difference between a UI-scraping bot and a native workflow node.

Robotic automation in the enterprise historically meant a bot that pretended to be a human: it opened a browser, clicked buttons, filled fields, and moved data between systems that would not otherwise speak to each other. That shape made sense when the only alternative was a four-month integration project per vendor. It makes much less sense inside a modern CRM where the records, the fields, the pipeline, the messaging layer, the assistant, and the forecasting are already in the same database. For a revenue team in 2026, robotic automation means two things. First, a set of specific bots that run on records continuously without a human needing to open the UI. Second, a canvas where an admin can compose new bots in minutes rather than scheduling a six-week RPA engagement. Strkr ships both. The bots live on the flow canvas as typed nodes, read the same records the humans read, write to the same database the humans write to, and respect the same permissions. No desktop agent, no UI scraper, no second procurement cycle.

Lead routing bot

Every inbound gets an owner inside sixty seconds.

The routing bot reads territory rules, round-robin assignments, named-account mappings, and availability settings. A new lead on the web form lands with an owner before the SDR floor finishes their coffee. If the account is a known parent, the routing respects the hierarchy. If the primary owner is out of office, the backup picks up without a manager stepping in.

Deal update bot

Stale deals get a nudge, not a hall-pass.

The deal bot walks every open opportunity every morning. Deals past the stage SLA with no activity get a nudge to the owner. Deals in the final stage missing a close plan get a flagged task. Deals above a dollar threshold without a champion mapped get a prompt to add one. Managers stop playing audit police; the bot does the second-level check before the Monday review.

Renewal prep bot

Four months out, briefings on every renewal.

When a contract crosses the 120-day window, the renewal bot opens the renewal opportunity in the right stage, assembles a brief from usage and support history, drafts a renewal narrative, and lands a task on the CSM. The motion starts early because the bot made early the default rather than the exception that disciplined CSMs had to carve time for.

Support triage bot

Tickets land tiered, routed, and summarized.

An inbound ticket gets a severity label, a product-area tag, a quick extracted summary, and a routing decision in one pass. The agent opening the queue in the morning sees a sorted and labeled stack. Nothing sits in the catch-all queue waiting for a human to triage it before the real triage begins.

Pipeline hygiene bot

Fields missing, stages mismatched, owners stale.

The hygiene bot runs nightly across the pipeline. Deals in Negotiation without a close plan get a flag. Deals with no activity for 21 days get a stage-stall warning. Accounts missing a tier value get a reminder to the owner. The pipeline review stops being a hygiene exercise because the bot cleaned the obvious items overnight.

Forecast scrubber

Numbers that disagree with the deal get surfaced.

The forecast bot compares the rep-called forecast number against the model-called number for every deal in the window. Deals where the rep is calling commit but the model is calling at-risk land in a surfaced list for the manager. The forecast conversation opens on the real disagreements rather than reading every row from the top.

Expansion sweeper

Signals compound into a surfaced play.

The expansion bot walks every active customer. Accounts hitting a seat ceiling, adding a strategic stakeholder, or activating a feature flag that correlates with cross-sell get a surfaced play with the suggested next step and the draft email. The AE opens an actionable queue, not a list of accounts they need to go read before they know what to do.

Reporting bot

The weekly brief, written while the team sleeps.

A reporting bot runs Sunday evening. It composes the weekly pipeline brief, the win-rate dashboard snapshot, and the churn watchlist. Each one lands in the right inbox at 06:30 Monday morning. The leadership team opens Monday with the receipts, not a request to the BI analyst to run the same six queries they ran last week.

Record merger

Duplicate accounts, resolved by rule.

The merge bot walks the account book for duplicates, matches by domain and legal name against the configured threshold, and either auto-merges or surfaces the pair for a human decision. Hierarchies, custom fields, activity history, and relationship data preserve across the merge. The book stays clean without an ops person running the dedup query on a quarterly cadence.

What a bot step looks like on the canvas

The anatomy of a Strkr bot that is not an outbound HTTP call.

The classic RPA story put the bot in a desktop that logged into every application a human would log into. That shape works when the applications are not integrated. Inside Strkr, the pipeline, the messaging, the assistant, the forecasting, and the reporting share a database and a permission model. A bot step is not a UI-scraping emulator; it is a typed node on the flow canvas that reads records, calls Strkr AI when it needs reasoning, writes back under permissions, and emits audit log entries along the way. The admin building a new bot sees the same canvas, the same node palette, and the same run log as every other flow in the tenant. Nothing goes to a second product.

Trigger

Record change, schedule, API event, or button.

Every bot starts on a trigger. A record change on a given object. A scheduled run (hourly, nightly, weekly). An inbound API event from an external system. A button click from a user with the right permission. The admin picks the trigger from a palette and the bot starts running the next time the trigger fires, with no re-deployment step.

Read nodes

Pull records with typed queries.

A bot that works a deal reads the deal, the related account, the related contacts, and any required custom objects in a single read step. The query is typed; the next node sees shaped data rather than a raw blob. The admin never writes a WHERE clause the system cannot explain and never joins across objects the permission model will not permit for the service account.

Reasoning nodes

Strkr AI, native, no credit meter.

When the bot needs to reason, it calls a Strkr AI step: Classify, Extract, Draft, Score, Summarize, Decide, Compare, or Verify. The step honors the same contract as every other node: typed input, typed output, retries, idempotency, guardrails, and audit log entries. No webhook to a separate AI service, no second billing meter.

Write nodes

Permission-aware field updates.

Write nodes update fields on records under the service account permission. The admin configures a per-flow allowlist of fields the bot may touch. The validator refuses to save a flow that writes outside the list. The record audit trail shows which bot wrote which field at which time, so compliance can walk a change back to the originating automation.

Branch and loop

Decisions and iteration without code.

Standard flow primitives apply: if/else branches on typed conditions, map loops over collections of records, early exits on a sentinel value. The admin composes a non-trivial bot entirely in the visual canvas. Complex logic that would be a hundred lines of JavaScript in a competing RPA script is twelve nodes on a Strkr flow.

External actions

HTTP, Messaging, Email, Document.

When a bot needs to reach out, it uses typed action nodes. Send SMS routes through Strkr Messaging. Send Email composes through the native email stack with signatures, tracking, and reply threading. HTTP request calls out to an allowlisted external endpoint. The admin configures each action once; the bot picks it up with no additional glue.

Run log

Every bot run leaves a visible breadcrumb trail.

The run log for the bot shows every node execution with inputs, outputs, elapsed time, and status. A failed run exposes the exact node that failed and the exact error message. Debugging a bot is the same experience as debugging a stored procedure. There is no vendor dashboard three logins away hoarding the information.

Pause and resume

Bots can wait for a human and continue.

A bot can pause for a human approval, resume on a timer, or wait for a specific record change. A renewal bot drafts a pitch, waits for the CSM to approve, and then schedules the follow-up. The pause-and-resume primitive turns a long-running motion into one bot rather than a chain of brittle webhook calls between separate systems.

Error handling

Named failure branches on every node.

Every node has an error branch. A failed Strkr AI classification routes to a human review branch. A failed external HTTP call routes to a retry with backoff. A failed write routes to a flagged task on the admin. The bot has a defined behavior under failure, which is the thing that distinguishes a production bot from a brittle demo.

Robotic automation versus a human workflow

The shape of the work the bot takes off the team plate.

The question every leader asks the first week after installing robotic automation is: what did it actually take off my team plate. The useful response is a specific list, measured per role. SDRs lose the manual lead-triage morning. AEs lose the pipeline hygiene burden on Mondays. CSMs lose the fire-drill renewal starts in the final week. Support leads lose the inbound queue sorting pass. Managers lose the dashboard-assembly before every 1:1. Each one of those tasks sits between twenty minutes and two hours a week per person, and the bots pick up the mechanical half so humans spend time on the judgement half. The table below is the honest estimate on a 40-rep floor, drawn from the tenants who have run this for a quarter or more.

SDR triage

From 90 minutes a morning to 20.

An SDR used to arrive to a raw inbox of unenriched leads and spent 90 minutes qualifying, scoring, and routing by hand. The bot does the triage overnight. The SDR opens an already-tiered queue, calls the As first, and spends the morning on conversation rather than classification.

AE Monday hygiene

From 2 hours a Monday to 15 minutes.

An AE used to spend two hours every Monday scrubbing their pipeline before the forecast call: missing close plans, stale deals, mislabeled stages. The hygiene bot flags each issue overnight. The AE opens a list of flagged exceptions and spends fifteen minutes resolving them rather than two hours finding them.

CSM renewal prep

From a week of panic to a month of motion.

A CSM used to realize a renewal was 30 days out and scramble to assemble the pitch. The renewal bot opens the opportunity at 120 days, drafts a narrative, and lands a task. The CSM spends four months on the motion with four prepared conversations instead of one week on a hurried close.

Support triage

From a 30-minute morning sort to immediate work.

A support lead used to spend thirty minutes each morning tagging and routing the overnight ticket inflow. The triage bot writes the severity and the product area while the ticket is still in flight. The lead opens the queue to already-tiered rows and starts on the P1 at 09:01.

Manager pre-reads

From dashboard digging to a two-page brief.

A manager used to spend forty minutes before each weekly 1:1 digging the pipeline for context on the five deals they wanted to discuss. The reporting bot composes a one-page brief for every rep report every Sunday evening. The 1:1 opens on the deals that need coaching, not on orientation.

Finance reconciliation

From Friday-afternoon exports to continuous reconciliation.

A revops partner used to export the pipeline and reconcile against the forecast every Friday. The reconciliation bot runs continuously and flags the deals where the number has drifted from the stage definition. The Friday export becomes a sanity check, not a four-hour investigation.

Dedup discipline

From quarterly scrubs to always-clean book.

An ops team used to run a dedup sweep once a quarter and lose a weekend to the merge list. The merge bot walks the book nightly, auto-merges by rule, and surfaces the ambiguous pairs. The book stays clean without a quarterly ritual. New reps join a book that is already in order.

Pipeline hygiene coverage

From 60 percent clean to 95 percent clean.

The pipeline that used to show 60 percent of deals with a close plan now shows 95 percent because the bot flags the missing ones every day. The hygiene metric is not a willpower exercise. It is a bot that moves the number because the humans see the flag the morning the field is still missing.

Reclaimed selling hours

Forty-plus hours a week across a 40-rep floor.

The arithmetic on a 40-rep floor adds to roughly forty hours a week of reclaimed capacity. Not from a dramatic replacement of human work, but from the quiet subtraction of the mechanical half of five motions. The team runs the same hours and spends more of them on conversation and judgement.

Governance for robotic automation

The posture that lets the bots run in production.

The reason most RPA deployments stall after six months is not a technology failure. It is a governance failure. The bots get written by whichever admin had capacity that quarter, nobody tracks which bots touch which fields on which objects, and the first time a bot writes something questionable in production, the team shuts the whole program off because nobody can bound the blast radius. Strkr ships the governance posture inside the product. Permission allowlists, approval workflows on changes to production bots, prompt and node version history, residency pinning, PII masking, rate caps, and a per-tenant execution log. The admin configures the posture once and every new bot inherits it. The compliance review on a new bot takes minutes rather than weeks.

Field allowlists

The bot may only touch fields the admin named.

Per object, the admin lists the fields a bot is allowed to write. The validator refuses any flow that writes outside the list. Compliance walks the allowlist in plain English rather than reading flow source. A new field added to an object is implicitly out of scope until an admin adds it to the allowlist.

Production marking

Flows marked prod require a second approver.

Any bot marked production requires a second admin to approve the diff before the change promotes. The diff view shows node changes, prompt changes, allowlist changes, and schedule changes. Nothing slides into prod on one keystroke, and emergency changes go through the same gate with a visible override log.

Rate caps

Cap the bot run count per minute.

Every bot carries a rate cap. The default caps ship conservative so a misconfigured upstream trigger cannot fire a million runs on a Saturday. A spike that would have crashed a brittle RPA installation routes to the overflow queue and surfaces a flag for the admin on Monday morning, which is the sane fallback.

Residency pinning

Runs stay in region.

A bot pinned to a region executes, reads, writes, and logs inside that region. The admin configures the posture at the tenant level, every new bot inherits, and the validator fails any flow that attempts to escape the pinned region. The EU customer running a bot on an EU record never sees the data leave the region, which is the compliance posture a European admin is required to maintain.

PII masking

Sensitive fields never reach the model.

Fields marked PII mask before any Strkr AI step inside the bot sees the record. The step processes the row, writes the allowed outputs, and never had access to the forbidden fields. The posture lives in the step, not in a wrapper the admin can bypass by mistake, which is where PII leaks usually originate in competing products.

Audit log

Every bot run leaves a row.

The audit log carries one row per bot run with the trigger, the service account identity, the input, the resulting field changes, and the elapsed time. Investigations walk the log in Strkr; nothing lives in a vendor console the SOC has to pull a quarterly export from. The log is retained per the tenant retention policy, not the vendor default.

Approvals in-flow

A bot can require a human sign-off.

A bot step can pause the flow and emit a task to a configured approver. The approver reviews the proposed change, approves or edits, and the bot resumes. Approval tasks live in the standard task inbox, not in a separate workflow queue the approver would have to learn.

Prompt version history

Reasoning changes carry a diff.

Prompts inside bot reasoning steps behave like source code. Every save creates a version with a diff. The admin pulls up any prior version, compares it against the current one, and reverts in two clicks. Audits connect disputed bot outputs to the exact prompt version that produced them.

Kill switch

One toggle to stop a misbehaving bot.

Every bot has a kill switch on the admin view. One click pauses the bot across the tenant immediately and emits a system notice to every admin. The paused state preserves the run history and the config, so the admin diagnoses from a frozen state rather than a running one. Nothing is lost; everything is paused.

How robotic automation plugs into the rest of Strkr

The bots talk to every object, every surface, every tier.

The thing a native robotic automation layer gets right that a desktop RPA tool cannot is end-to-end integration with the records the humans work. A bot on a Strkr deal is not pretending to be a human clicking through the Salesforce UI; it is reading and writing the same database Strkr serves to its own API. The bot talks to the forecast, the messaging layer, the documents module, and the reporting fabric with no glue in the middle. The relationships below are the ones admins exercise most.

CRM records

Account, deal, lead, contact, custom objects.

Bots read and write every object the humans touch, with field-level and row-level permissions enforced for the service account. A bot updating a deal looks exactly like a rep updating a deal in the audit log, except the actor is the named service account rather than a person.

Strkr Messaging

SMS and MMS as a native action node.

A Send SMS node routes through Strkr Messaging with the full consent, opt-out, and quiet-hours policy applied. The bot composing a renewal nudge over text does not need a separate carrier config, a second compliance review, or a separate audit log. One policy, one log, one place to think about.

Forecasting

Bot-updated fields flow into the forecast.

When a bot updates a deal risk score or shifts a close date, the forecast rollup reflects the change on the next read. There is no nightly batch job stitching the bot outputs back into the forecast model. The forecasting page and the automation canvas share a database.

Reports

Every bot-written field is a report column.

The field a bot wrote is a report column the admin can pivot, filter, and chart. Build a dashboard on bot-written risk scores. Pin a chart on bot-triggered churn tier movements. The output of a bot is first-class data, not a side-table that only the bot owner understands.

Documents module

Bots read the wiki for context.

A bot composing a support response reads the current troubleshooting article from the Strkr Documents module. A bot drafting a sales email reads the current objection-handling note. The retrieval is native. The bot references versioned content; a wiki edit flows through to the next bot run without a sync job in the middle.

Projects module

Sprint, release, and backlog bots.

Projects admins run bots on sprint and release records with the same canvas, the same node palette, and the same governance posture. A sprint recap bot composes a Friday summary. A release bot drafts notes from merged pull requests. The automation story is one story across the product.

API ingress

External events trigger native bots.

An external system posts an event over the Strkr API, the matching bot runs on the payload, and the response threads back through the same API. The telemetry pipeline from a product feature feeds a usage-signal bot that nudges a save play. The API is the integration surface; there is no middleware.

Scheduled runs

Bots run on cron, not just triggers.

Schedule a bot nightly, hourly, or at a specific hour each weekday. The weekly reporting bot runs Sunday evening and the pipeline brief lands at 06:30 Monday. The scheduler is first-class on the flow canvas, not a separate scheduling product.

Dev to prod promotion

Three lanes with real approvals.

Bots carry a dev, staging, and production lane. Changes move through each boundary with approvals. Prod never surprises the team because staging reads exactly the same version prod will see next. The promotion is a product feature, not a Pulumi script the admin maintains on their laptop.

Robotic automation that lives on the record, not on a desktop pretending to be a human.

Lead routing, deal updates, renewal prep, support triage, pipeline hygiene, forecast scrubbing, expansion sweeps, reporting, and record merging. Nine production-grade bots that ship native to the CRM with full observability, retries, residency pinning, and no credit meter.

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Common questions

What buyers ask about this feature.

What is robotic automation and how does the Strkr version differ from classic RPA?

Robotic automation is the set of bots that run on records without a human opening the UI. Classic RPA installs a desktop agent that pretends to be a human clicking through unrelated applications. That shape was useful when the applications had no integrations and no shared database. Strkr is a CRM where the pipeline, messaging, assistant, forecasting, documents, and reporting share a database and a permission model, so the bots live inside the product as typed workflow nodes rather than as UI-scraping scripts. The admin builds a bot on the same canvas as every other flow, and the bot reads and writes the records directly, with full observability, retries, audit logging, and governance.

Which robotic automation bots does Strkr ship out of the box?

Nine production-grade bots: lead routing (owner inside 60 seconds, hierarchy-aware), deal updates (stale deals, missing close plans, champion gaps), renewal prep (120-day briefings), support triage (severity, product area, routing), pipeline hygiene (field completeness, stage mismatches), forecast scrubbing (rep-called vs model-called disagreements), expansion sweep (seat ceiling, stakeholder, feature-flag signals), reporting bots (weekly brief, pipeline snapshot, churn watchlist), and record merger (duplicate book cleanup). Each one ships configurable, runs under the tenant governance posture, and is editable on the standard flow canvas rather than in a separate RPA studio.

How is a Strkr bot step different from a flow that just calls an external AI service through a webhook?

A Strkr bot step is a native node on the flow canvas with typed inputs, typed outputs, retries, idempotency keys, timeouts, guardrails, and audit log entries. A webhook to an external AI service is an opaque HTTP call: retries double-send, outputs are untyped blobs the next step has to parse, and the audit trail lives in two places. The native step inherits the service account permissions, so it cannot touch fields outside the configured allowlist, and it participates in the same transaction as the surrounding write nodes. The admin thinks about the step the way they think about a database write rather than the way they think about a glue script.

What governance controls does Strkr apply to robotic automation bots in production?

Six controls apply by default. Field allowlists per object limit which fields a bot may write. Production marking requires a second admin to approve the diff before any change promotes. Rate caps protect against misconfigured upstream triggers firing in a loop. Residency pinning keeps execution, data, and logs inside a chosen region, with the validator refusing to save flows that escape it. PII masking hides sensitive fields from reasoning steps. The audit log records every bot run with the trigger, service account, input, resulting changes, and elapsed time, retained per the tenant retention policy. Admins also get a kill switch that pauses a bot across the tenant in one click.

How much work does robotic automation actually take off a revenue team plate?

On a 40-rep floor the typical reclaimed capacity is roughly forty hours a week across the organization. SDRs save about 70 minutes per morning on lead triage. AEs save about 1 hour 45 minutes per Monday on pipeline hygiene. CSMs save a week-long renewal fire drill per renewal by starting the motion at 120 days instead of 30. Support leads save about 30 minutes per morning on queue triage. Managers save about 40 minutes per 1:1 on pre-read assembly. The hours come from subtracting the mechanical half of five motions, not from replacing human judgement, and the team spends more of the same hours on conversation.

Can we build custom robotic automation bots or are we limited to the nine prebuilt ones?

Any admin with the flow builder role can compose new bots on the canvas. The nine prebuilt bots ship enabled and configurable; the admin can clone any of them as a starting point. New bots use the same node palette: triggers (record change, schedule, API event, button), read nodes, reasoning steps (Classify, Extract, Draft, Score, Summarize, Decide, Compare, Verify, Chain), branch and loop primitives, write nodes under permission allowlists, external action nodes (SMS, email, HTTP), pause-and-resume, and typed error branches. The admin builds a non-trivial bot in minutes without leaving the Strkr UI, and the bot inherits every governance control configured for the tenant.

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