Feature · Process Automation Solutions

Process automation solutions that treat the record as the system of record.

Triggers on every event, actions on every surface, approvals where the money moves, exception queues where the shape breaks, and an audit log that holds the whole chain of decisions. Strkr ships the flow engine, the AI assist, and the open API native on every paid tier so the automation program grows without an integration tax.

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What a process automation solution actually has to carry

Trigger, action, approval, exception, audit, retry, and reporting.

The honest definition of a process automation solution is a short list of capabilities that each have to work in production at real volume. Trigger on real events. Act on real surfaces. Pause for human approval where the money or the risk crosses a line. Catch exceptions in a reviewable queue. Log the full chain of decisions. Retry on transient failure. Report what ran, what succeeded, what did not. If any of those seven pieces lives in a separate tool or a middleware layer, the automation stops being a solution and starts being a tax. Strkr builds all seven native on top of the record store.

Event triggers

Real events, not polled snapshots.

Flows trigger on the real event stream the record produces: field change, record create, record delete, stage advance, SLA breach, inbound email, inbound SMS, webhook arrival, custom event emitted by the app layer. The trigger fires inside milliseconds of the event. No five-minute polling cycle. No stale snapshot driving the action.

Native actions

Every surface the record touches.

Flow actions span the whole stack: update a field, create a record, send an email, send an SMS, create a task, book a meeting, fire a webhook, run an assistant draft, enroll in another flow, suspend the record, archive the record. The action list reads the real capability surface, not a filtered subset the vendor chose.

Approval gates

A human step on the sensitive moves.

Any flow step can require a human approval before continuing. The approver reads the context, the proposed action, and any assistant draft, then approves, edits, or rejects. The approval logs with the actor, the timestamp, and the version hash of the step that was approved so compliance reviewers can trace sign-off per record.

Exception queues

When the shape breaks, where the record lands.

When a flow step fails validation, hits a permission block, or encounters a condition the admin flagged for review, the record moves to the exception queue. The ops lead works the queue, resolves the exception, and the flow resumes from the paused step. Nothing dies silently in a stalled state.

Retry logic

Transient failures do not kill the run.

Flow steps that fail on transient conditions (webhook timeout, upstream rate limit, temporary permission flap) retry with exponential backoff up to a configured ceiling. Persistent failures route to the exception queue after exhaustion. The retry log is auditable so the ops team can distinguish flaky infrastructure from a real failure in the logic.

Audit log

Every run, every change, every actor.

The audit log carries every flow run, every action executed, every field touched, every approval granted or denied, and the actor identity for each. The log is tamper-evident and sits inside the SOC 2 control set. A compliance reviewer can walk any process end to end and see the full chain of decisions.

Observability

Dashboards for the automation program.

The observability dashboard shows flow run rate, step success rate, exception volume, approval latency, retry rate, and total records touched. The ops lead monitors the automation program the way the engineering team monitors a production service. Problems surface before they turn into a weekly fire drill.

Shadow mode

Run the flow without executing.

A new flow or an updated flow can run in shadow mode for a configurable window. The system computes the actions it would have taken and logs them without executing. The ops lead reviews the shadow log and decides whether to flip the flow to live. Shadow mode catches the quiet failures that only reveal themselves at volume.

Version history

Every flow change stored and revertable.

Each flow save produces a version. The diff shows which steps changed, which conditions moved, which copy was rewritten. Rolling back is one click. The audit log carries the actor, the timestamp, and the change scope so the full life of a flow is reconstructible from the version history alone.

Solution shapes that actually ship in week one

The common processes production teams wire up first.

A process automation solution earns the seat in the first thirty days by covering the common shapes revenue and operations teams run constantly. These are the flows most Strkr customers build in the first month of use. Each one carries a specific trigger, a specific action set, a specific approval posture, and a specific exception handler. The whole catalog composes on top of the native flow engine and the native record store, so admins build fast and audit easy.

Lead routing

Inbound to the right rep in two seconds.

Trigger on new lead. Branch on tier, territory, named-account flag. Assign to the right rep in the round-robin. Fire a Slack notification. Create a 15-minute SLA task. If no response, escalate to the SDR manager. The route runs in milliseconds and respects the real org chart, not a static list.

Stage transitions

A deal moves, the stack updates.

When a deal advances to proposal stage, create a proposal document from template, assign the proposal task to the sales engineer, email the prospect the standard discovery recap, and set the next-step field to the agreed close date. Everything that should fire when the deal moves actually fires, without the rep remembering to do each one.

Data hygiene

Duplicates found, merges proposed, records enriched.

Nightly sweep for duplicate leads and contacts. Score duplicate confidence. Propose merges for review. Enrich missing firmographic fields from the integrated provider. Flag records with suspicious data (test emails, blocked domains, incomplete titles). The ops lead works the queue weekly rather than every record manually.

Discount approval

Draft the memo, route the sign-off.

A rep requests a discount above threshold. The assistant drafts the justification memo based on deal context. The sales manager reviews, approves, and the discount applies on the quote. The approval and the memo log on the deal for the quarterly discount audit. The process ran where the deal already lives.

SLA enforcement

A ticket missed, the manager knows.

When a support ticket crosses an SLA threshold (first response, resolution, escalation), the flow pings the owner, surfaces the ticket on the manager dashboard, and runs the appropriate escalation. The SLA miss becomes visible when it is still savable, not after the customer calls to complain.

Renewal readiness

A contract approaches, the prep starts.

When a contract hits 120 days from end date, open a renewal opportunity in the right stage, generate a renewal brief, assign a prep task to the CSM, send a value-recap email to the primary champion. The motion starts four months out, not the week before, which materially moves renewal rates.

Churn save

A red tier triggers the save plan.

When an account health score drops to red, create a save task on the CSM, draft a specific save offer based on the driving signals, escalate to the VP of success after 48 hours without action, and schedule a 30-day follow-up for the save motion. The save program runs where the risk already lives.

Order kickoff

Closed-won becomes a running engagement.

When an opportunity closes won, trigger kickoff: create the implementation project, assign the CSM, send the kickoff email with the implementation playbook, schedule the kickoff call window, generate the welcome packet. The handoff from sales to post-sales is one flow run, not a four-tool handoff that takes a week.

Compliance review

A sensitive field changes, legal gets a ping.

When a field flagged as sensitive changes (contract term, data residency commitment, regulated-industry tag), notify the legal reviewer, hold the record for approval, and log the review in the audit trail. The compliance posture holds even when the field change happens inside a different automated flow.

How the solution composes with the rest of the stack

Open API, native integrations, no connector tax.

Process automation solutions only earn the long-term seat if they integrate well with the rest of the stack. The sealed-box pattern (every integration goes through the vendor marketplace, every connector carries a fee, every workaround is a professional-services engagement) is the pattern that eventually gets ripped out. Strkr ships an open REST API, documented webhooks, native messaging, and a cross-module shared record so the automation layer sits inside the broader stack rather than next to it.

Open REST API

Every object, every event, no feature paywall.

The REST API covers every object, every field, every custom field, every event, and every flow and assistant action. OAuth 2.0 with scoped tokens. Rate limits sized for real production integration load. Downstream systems read and write at whatever cadence the engineering team needs without a connector purchase.

Signed webhooks

Push, do not poll.

Every record event (create, update, delete, custom) can fire a signed webhook to a configured endpoint. The payload carries a timestamp, a replay token, and a signature verifiable with the shared secret. The admin dashboard shows recent deliveries with success, failure, and retry status so integration failures surface early.

Native messaging

SMS and email inside the automation.

Strkr Messaging is the native SMS and MMS layer. Email is the native email layer. A flow step sends either channel without a third-party connector. Delivery status, consent, opt-out, and quiet hours all respect the native compliance posture inside the same audit log.

MCP server

Agent frameworks read the record store.

Strkr publishes a Model Context Protocol server for teams running agent frameworks that need live access to the record store. The MCP endpoint respects the same permission model as the REST API and the UI. External agents see only what the connecting user is permitted to see.

CSV workflow

Bulk import and export with full audit.

For integrations that do not warrant a live API connection, the import wizard reads CSV, maps columns to fields, respects validation rules, and writes to the record store with a full run log. Export runs any list view or report into CSV with the same filter and permission posture.

Warehouse ingestion

Snowflake, BigQuery, Redshift, documented.

Standard ingestion patterns and connectors ship for the major data warehouses. Data lands in the warehouse at whatever cadence the data team configures. The BI tool reads from the same source of truth as the CRM so dashboards do not drift out of sync with the operational system.

Shared record store

CRM, projects, marketing, messaging, one object.

Every module in Strkr (CRM, Marketing, Projects, Messaging, Documents) reads from and writes to the same record store. A process automation flow in marketing can read a project status, update a CRM field, send an SMS, and attach a document in one run. The shared store removes the need for an integration layer between the modules.

Permissions model

Automation sees only what the actor sees.

Every flow runs under the identity of the triggering event (or a service account the admin configures). The permission model applies. Field-level permissions, record-level permissions, and sharing rules all respect the actor. The automation cannot leak data past the permission boundary even on an admin-authored flow.

Documents module

Attach, draft, route for signature.

A flow can draft a document from template, attach it to the record, route it for internal review, and send it out for signature through the integrated e-signature workflow. The document lives in the records module alongside every other attachment, with the same permissions and the same audit log.

The AI assist on top of the engine

Strkr AI inside the flow, not a separate SKU.

The AI assist in modern process automation solutions is the capability that turns a deterministic engine into a system that can handle fuzzy inputs. Strkr AI runs inside the flow engine as a composable action step. The assistant drafts, scores, summarizes, flags, and classifies in context, with the output targeted at the right field or the right review queue. The whole surface is included on every paid tier with no credit meter.

Draft a message

Email or SMS in the rep voice.

A flow step can call the assistant to draft an email or an SMS in the configured rep voice using the real record context. The draft lands in the review queue or auto-sends based on the configured policy. The admin can define draft style, tone, and length per workflow.

Score a record

A number on fit, intent, risk, health.

The assistant computes a score (lead fit, deal risk, account health, ticket urgency) and writes the result to a configured field. The score respects a weighting the admin set and ships with the top three driving signals in plain English for the audit log.

Summarize a record

Three paragraphs on the ninety days.

For records with long histories (accounts, open support tickets, long-running projects), the assistant summarizes the recent activity into a two or three paragraph brief. The brief lands in a configured field or an attached note. The CSM or AE reads the brief before the call rather than scrolling the timeline.

Flag an exception

The record that does not fit the shape.

For queues where the ops lead needs the three records that break the pattern rather than the full list, the assistant sweeps and flags with a one-sentence reason. The flagged list sits at the top of the queue so the ops team works the real exceptions first.

Classify

Which bucket, with the reason.

For records that need classification (support ticket topic, inbound lead segment, document type), the assistant classifies and writes the result to a field. The classification ships with the confidence score so low-confidence classifications route to human review while high-confidence classifications flow through automatically.

Enrich

Fill missing fields from context.

For records with sparse data, the assistant drafts likely values for missing fields based on the available context and the enrichment provider output. The draft values route to review before committing. A sparse lead becomes complete without the SDR writing every field by hand.

Extract

Pull fields out of unstructured text.

For inbound emails, inbound SMS, meeting notes, call transcripts, and attached documents, the assistant extracts the named fields the admin configured (budget, authority, need, timeline, competitors). The extracted fields flow to the record with the source citation so the rep can verify.

Prioritize

Which record first, which record last.

For queues sorted by human intuition rather than a single number (SDR daily list, CSM save list, support escalation queue), the assistant ranks the records by expected value and surfaces the top of the queue. The sort respects configurable business rules so the AI ranking matches the real revenue priorities.

Explain

Why the output looks the way it does.

Every assistant action ships with an explanation showing the signals it used, the weighting it applied, and the confidence score. The explanation lives on the record alongside the output. The reviewer argues with the reasoning, not the black box, and the audit log carries the explanation forward.

Picking a process automation solution

The buyer checklist the pitch does not cover.

The decision to pick a process automation solution comes down to a short checklist the vendor pitch tends to skip. These are the questions the ops team should press on every finalist before signing. Strkr answers all nine with yes, no asterisk, so a prospect can compare apples to apples against the alternative stack they are considering.

Native vs middleware

Does the engine live inside the record store.

A flow engine that lives inside the CRM reads the record in real time, writes atomically, and respects the audit log natively. A flow engine that lives outside the CRM syncs on an interval, writes through a connector, and drifts. The native pattern is the only one that stays coherent at scale.

Pricing shape

Per seat or per run or per action.

Per-run pricing penalizes volume. Per-action pricing penalizes complexity. Per-seat pricing with an unlimited action count rewards the team that automates aggressively. Strkr runs on per-seat pricing with no action meter on flows and no credit meter on the assistant.

Open API posture

Can engineering build custom integrations.

Open REST API, documented webhooks, standard OAuth, published rate limits, and a Model Context Protocol server. Everything the integration team needs to build without a vendor marketplace or a connector purchase. The open API is the long-term insurance against vendor lock-in.

Audit trail

Who did what, when, to which record.

A tamper-evident audit log covering every flow run, every action, every approval, every record change, and every actor identity. The audit log is the first thing a compliance reviewer looks at and the first thing an ops leader needs when a bad run has to be reversed.

Permission model

Does the automation respect sharing.

Flows run under the identity of the triggering actor. Field-level permissions, record-level permissions, and sharing rules all apply. The automation cannot leak data past the permission boundary. Admin-authored flows cannot grant visibility to users who should not see the touched records.

Shadow mode

Can the admin test without executing.

A shadow mode that lets new flows and updated flows run against real records without executing the actions, with a shadow log the ops lead can review before flipping to live. Shadow mode catches the silent failures that only reveal themselves at production volume.

Reversibility

Can the admin undo an automated action.

Every automated action should produce an undo record so the admin can revert the change within a configured window. The alternative is a bad flow run that leaves a hundred records in a broken state that takes a week of engineering time to fix manually.

HIPAA and SOC 2

Compliance posture the enterprise buyer needs.

HIPAA-compliant deployment with a signed Business Associate Agreement for qualified customers. SOC 2 Type II program in progress with an external audit firm. The compliance posture matters for enterprise and regulated-industry buyers and is non-negotiable past a certain segment.

No Zapier dependency

First-class integrations, not middleware.

Strkr ships every integration as first-class native code with API, webhooks, and KMS-encrypted credentials. The pattern avoids the middleware tax where every connected system adds a per-run cost and a reliability dependency on a tool that was never designed for production-grade automation.

A process automation solution that sits inside the record store, not next to it.

Flow engine, AI assist, exception queues, approval steps, open API, native messaging, and audit log all ship on every paid tier. No run meter, no action meter, no credit meter on the assistant. Open your real workflow and see how fast the first flow goes live.

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Common questions

What buyers ask about this feature.

What is a process automation solution and what should it include?

A process automation solution is a platform that reads events from the business system, runs configured actions in response, pauses for human approval where sensitive moves happen, catches exceptions in a reviewable queue, retries transient failures, logs every decision for compliance, and reports what ran. The seven capabilities (trigger, action, approval, exception, retry, audit, report) each have to work in production at real volume. If any of them lives in a separate tool or a middleware layer, the automation stops being a solution and starts being a tax on every integration decision downstream. Strkr builds all seven native on top of the record store with the same permission model, the same audit log, and the same reporting surface as the rest of the CRM.

What processes do teams actually automate in the first month on Strkr?

The nine processes most Strkr customers build in the first month are lead routing (inbound to the right rep in two seconds), stage transitions (a deal moves and the stack updates), data hygiene (duplicate detection, enrichment, suspicious-record flagging), discount approval (drafted memo plus manager sign-off), SLA enforcement (ticket miss triggers escalation), renewal readiness (120-day warmup motion), churn save (red-tier accounts trigger a save plan), order kickoff (closed-won becomes a running engagement), and compliance review (sensitive field change notifies legal). Each one carries a specific trigger, action set, approval posture, and exception handler on top of the native flow engine.

How does the Strkr automation layer integrate with the rest of the stack?

Strkr ships an open REST API covering every object, event, custom field, and flow or assistant action, signed webhooks on every record event, a Model Context Protocol server for teams running agent frameworks, documented ingestion patterns for the major data warehouses (Snowflake, BigQuery, Redshift), native email and SMS layers that do not require a third-party connector, and a shared record store across the CRM, Marketing, Projects, and Messaging modules. There is no middleware tax, no connector purchase, and no dependency on a Zapier-shaped integration platform. Every integration is first-class native code with OAuth 2.0, published rate limits, and KMS-encrypted credential storage.

What does Strkr AI add inside the flow engine?

Strkr AI runs inside the flow engine as a composable action step. The assistant drafts emails and SMS in the configured rep voice, scores records on fit, risk, health, and urgency with the top three signals in plain English for the audit log, summarizes long record histories, flags exceptions, classifies records into configured buckets, enriches missing fields, extracts fields from unstructured text (inbound emails, meeting notes, call transcripts), prioritizes queues by expected value, and explains every output with the signals and the weighting it used. The assistant runs on every paid tier with no credit meter and no separate SKU, which means the flow engine and the AI assist share one pricing model.

How does Strkr keep the automation program auditable and reversible?

Every flow run writes to a tamper-evident audit log with the actor, the timestamp, the touched record, the action executed, the field changes, and any approval granted or denied. The log sits inside the SOC 2 Type II control set. Every automated action produces an undo record that can revert the change within a configured window, so a bad run does not leave records in a broken state. New flows and updated flows can run in shadow mode for a configurable window to see what the automation would have done without executing. Admins can mark specific fields as human-only so the automation can draft a change but cannot commit without an approval. The combination keeps the program defensible when compliance reviewers walk the trail.

Does process automation ship on every tier or is it a premium add-on?

The process automation engine, the AI assist, the exception queue, the approval steps, the open API, the webhook surface, the native messaging layer, and the audit log all ship on every paid tier at no extra charge. There is no per-run meter on flows and no per-action credit meter on the assistant. Admins can pick the underlying model for specific assistant workloads to tune cost against quality, but the base automation capability sits inside the seat price with no action-count billing. HIPAA-compliant deployments with a signed Business Associate Agreement are available for qualified customers, and SOC 2 Type II is in progress with an external audit firm.

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