Feature · Digital Process Automation Software

Digital process automation software with the record built in.

Most digital process automation software ships a flowchart canvas and a long list of connector logos. The flowchart draws fine. The hard part shows up six months later when the ops lead needs to answer why a flow fired, who approved what, which record version was in effect at run time, and how the policy that governed the run has changed since. Strkr builds digital process automation around the typed CRM record so the flow, the approval, the document, the AI reasoning, and the audit trail all land on the same object. The result is software that holds up under compliance review, not just the first demo.

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What digital process automation software has to be

Seven traits that separate real DPA software from flow canvas demos.

A canvas with drag-and-drop nodes is table stakes. Real digital process automation software has to carry typed data through every step, enforce the right approvals, retain the audit trail, let the ops team edit without a release, and run on a predictable commercial model. Below are the seven traits a revenue team should check before buying.

Typed record native

The flow reads the schema, not a JSON blob.

Every flow run reads the typed CRM record (account, contact, opportunity, custom fields) with the schema in effect at run time. The flow does not pass around opaque JSON that only the author remembers how to parse. The ops lead editing the flow six months later sees the field types in the dropdowns and the editor flags any field that was renamed since the flow was written.

Approvals on the home

Approvers do not switch tools to decide.

Approval nodes drop a card on the approver home with the context: what is being approved, what the delta from standard is, which policy governs the decision, and which record the request is for. The approver clicks approve or reject on the home card. The flow resumes. The common failure where approvals pile up because the approver has to log into a separate tool does not happen.

Audit trail attached

Every run carries the full receipt.

Every flow run writes an audit event per step with the actor, the inputs, the outputs, the policy version, and the record version. A compliance query like "every discount approval over 25% in Q3" is a filter on the audit page, not a six-week engineering project. The trail is append-only and configurable per tenant up to the regulated horizon.

Policy versioning

The rules in effect at run time are preserved.

Approval rules, discount thresholds, routing logic, and clause libraries all version on save. A run that fired on 2026-03-15 evaluates against the policy that was live on 2026-03-15. The audit trail pins the policy version to the run. A regulator asking "what rule governed this approval" gets an answer, not a shrug.

Ops lead autonomy

Flow edits do not require a release.

The ops lead edits a flow in the UI, promotes to a shadow environment, runs a dry pass against last week traffic, reviews the diff, and promotes to production. No engineering ticket. No build pipeline. The flow versioning carries rollback. The common failure where a simple routing change takes a quarter because engineering is the only path to production stops.

Seat pricing flat

No per-run, per-task, or per-step fee.

Strkr prices the digital process automation layer at the seat level, flat. There is no per-run fee, no per-task fee, no per-step fee, and no "advanced automation" paywall. A team that runs ten thousand flow steps a day pays the same as a team that runs a hundred. The finance team stops rate-limiting the ops team on process automation economics.

Open API everywhere

Flows call out, systems call in.

Flows call outbound to any HTTP API with retries, idempotency keys, and typed responses. External systems call inbound through signed webhooks that trigger named flows. The open API covers inbound and outbound. The common failure where a vendor advertises "integrations" and ships three logos does not happen because the API is the integration layer.

The processes that live on the platform

Six revenue workflows that land on DPA software, day one.

Teams usually land on digital process automation software with a shortlist of workflows that have hurt enough to justify the migration. The six below show up on almost every shortlist. Each one maps to a prebuilt agent and a reference flow that a new team clones and tunes rather than building from scratch.

Lead routing

Owner assigned in under a minute.

Inbound leads route to the right owner based on territory, segment, product interest, and account ownership rules. The flow applies the typed account match, checks the round-robin bucket, and assigns the owner. The common failure where a lead sits in a queue for days because the routing was spreadsheet-based gets closed off on day one.

Discount approval

Threshold rules, policy versioned.

Discount requests route to the sales lead above 15%, to the CFO above 25%. The approver sees the opportunity, the deal context, the discount history for the account, and the current policy version. Approval or rejection resumes the flow and updates the opportunity. The deal does not stall on approval friction.

Quote to signed

Proposal, approval, DocuSign, back on the record.

Quote generation runs from the Products module. The proposal document ships to DocuSign or PandaDoc through native integrations. The countersigned PDF lands back on the opportunity. The audit trail carries the catalog version, the clause library version, and the signer chain. The quote-to-signed cycle time measures in days rather than weeks.

Renewal automation

Fires 90 days out, routes to CSM.

Renewal flows fire at the configured lead time (90, 60, or 30 days out), create the renewal opportunity, draft the renewal addendum from the current master agreement, and route to the customer success manager with the usage and health context attached. The renewal that gets forgotten until two weeks before expiry stops happening.

Onboarding handoff

Closed-won to kickoff in one surface.

When an opportunity closes won, the handoff flow creates the project, assigns the implementation lead, drops the onboarding checklist on the account, and sends the welcome packet to the customer. The implementation lead sees the full deal context on day one rather than reconstructing it from Slack threads.

Support escalation

SLA breach fires named flow.

Support tickets carry SLAs by tier (24 hours for premium, 72 hours for standard). An SLA breach fires an escalation flow that notifies the manager, adjusts the ticket priority, and surfaces the ticket on the executive dashboard. The common failure where SLA breaches get noticed on the weekly report rather than at breach does not happen.

The engineering that holds the software together

What makes the DPA software production-grade.

A canvas is a demo. A production digital process automation platform has to survive drifting schemas, policy changes, approver turnover, catalog updates, and ten-thousand-run scale. Strkr ships the primitives that keep the automation holding up as the business evolves.

Typed schema

Fields change, flows surface the drift.

When a custom field renames, the flow editor flags every flow that referenced the old name. The ops lead sees the broken reference before the flow fails at run time. The common failure where a schema change silently breaks seventeen flows and nobody notices until the Q3 close does not happen.

Idempotency built in

Retries do not double-process.

Every outbound call carries an idempotency key keyed on the flow run and the step. A retry on a transient failure does not create a duplicate record on the downstream system. The common failure where a Salesforce migration ends up with duplicate opportunities because a retry fired twice does not happen because idempotency is the default.

Shadow environment

Dry run before promote.

Every flow has a shadow environment that runs against the live record state without writing. The ops lead edits a flow, triggers a dry run on last week traffic, reviews the diff (what would have changed), and promotes to production. The common failure where a flow edit breaks the pipeline in production does not happen because the dry run surfaced the break.

Observability built in

Every step emits structured events.

Every flow step emits a structured event with the inputs, the outputs, the duration, and the outcome. The ops lead queries flow performance from the admin UI without writing SQL. The common failure where "the flow is slow" has no answer because the vendor does not expose observability does not happen because the events are first-class.

Permissions aware

The flow runs with the right identity.

Each step runs with the identity of the actor who triggered the flow, respecting the Strkr permission model. A rep triggering a flow cannot read fields the rep is not entitled to read, even inside the flow. The common failure where a flow bypasses permissions and leaks data to the wrong user does not happen because the identity propagates.

Error surfacing

Failed runs land on an owner, not an inbox.

A failed flow run creates an actionable alert on the flow owner home with the error, the record, the step, and a one-click retry. The common failure where errors go to a shared inbox nobody owns and get missed for weeks does not happen because errors land on a named owner.

Where teams land in practice

Three deployment patterns from live customers.

A 60-seat SaaS, a 180-seat professional services firm, and a 420-seat healthcare company all run digital process automation software on Strkr. The platform plumbing stays the same. The flow configuration flexes to the business. The compliance posture holds across all three.

SaaS pattern

High-velocity lead and deal flows.

A 60-seat SaaS runs the inbound lead routing flow, the discount approval flow, and the quote-to-signed flow across 300+ deals a month. The flows fire within seconds of the trigger. The sales ops lead edits routing rules weekly without filing an engineering ticket. The pipeline velocity improved measurably in the first full quarter.

Services firm

Approval-heavy, SOW-centric flows.

A 180-seat professional services firm runs the SOW generation flow, the change order flow, and the onboarding handoff flow. Approval routing is dense: service lead, delivery lead, finance, and sometimes legal. Approvers see the proposed document and the delta from standard on one card. The approval cycle shortened from eleven days to under three on the median change order.

Healthcare company

HIPAA-aware flows with BAA addendum.

A 420-seat healthcare company runs the proposal flow with the BAA addendum automatically appended for any customer that will process PHI. The clause library includes HIPAA-compliant data clauses. The audit log carries the chain of custody. Strkr is HIPAA compliant with a BAA available. The platform SOC 2 Type II attestation is in progress through 2026-Q4.

Weekly ops review

Flow performance reviewed every Monday.

Monday mornings, the ops lead opens the flow performance report, reviews the top five slow flows, the top five error-rate flows, and any policy versions that landed last week. The review takes under twenty minutes. The common failure where process automation drifts for a quarter before anyone notices does not happen because the review is scheduled.

Quarterly policy audit

Approval rules re-ratified every quarter.

Quarterly, finance and legal re-ratify the approval rules. Thresholds that have not fired in a quarter get reviewed. New edge cases from the quarter get folded in. The policy version increments. Every flow run after the increment evaluates against the new policy. Runs in flight carry the version they started on.

Compliance walkthrough

Audit log satisfies the regulator.

When a regulator asks what approval policy was in effect for a signed order on 2026-04-15, the audit log carries the policy version, the actor chain, the record version, and the Strkr AI reasoning if any was involved. The answer is a URL with filters, not a six-week engagement. Compliance walks the regulator through the trail in one meeting.

Digital process automation software that holds under compliance review.

Strkr runs flows, approvals, document generation, Strkr AI, and audit trail on the typed CRM record. No per-run fees. Flat $50 per seat. Open API inbound and outbound. HIPAA with a BAA, SOC 2 Type II in progress through 2026-Q4.

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Common questions

What buyers ask about this feature.

What is digital process automation software and how is it different from business process management?

Digital process automation software executes end-to-end business processes with the records, the approvals, the documents, and the audit trail in one place. Business process management, historically, focused on modeling and documenting processes with the execution happening in separate systems. Strkr collapses the two. The modeled flow is the executed flow. The approval policy is the executed policy. The template is the executed document. The audit log captures all of it. Teams that bought BPM for the modeling and then stitched execution across a dozen tools find the Strkr single-surface shape easier to operate and audit.

Does Strkr charge per flow run or per step?

No. Strkr prices digital process automation at the seat level, flat. There is no per-run fee, no per-task fee, no per-step fee, and no "advanced automation" paywall. A team that runs ten thousand flow steps a day pays the same as a team that runs a hundred. The common failure where the finance team starts rate-limiting the ops team on process automation economics does not happen on this pricing model. The seat price on the pricing page is the full price for the digital process automation capability.

Can the ops lead edit flows without a release cycle?

Yes. The flow editor is a self-serve UI with versioning, shadow-environment dry runs, and one-click promote. The ops lead edits a flow, runs the dry pass against last week traffic, reviews the diff, and promotes to production. No engineering ticket. No build pipeline. The versioning carries one-click rollback if the promote causes a regression. The common failure where a simple routing change takes a quarter because engineering is the only path to production stops on day one.

How does the audit trail hold up under compliance review?

Every flow run writes an audit event per step with the actor, the inputs, the outputs, the policy version, the record version, and any Strkr AI reasoning. The audit log is append-only with cryptographic integrity. No role, including root admin, can disable or redact. The retention window is configurable per tenant up to the regulated horizon. A compliance query like "every discount approval over 25% in Q3" is a filter on the audit page. Strkr is HIPAA compliant with a BAA available, and the SOC 2 Type II attestation is in progress through 2026-Q4.

What happens to in-flight flow runs when the policy or schema changes?

In-flight runs carry the policy version and the schema version they started on. A policy change does not retroactively alter runs already in progress. A schema change does not corrupt mid-flight record reads. The audit trail pins the versions to each run, so a regulator or an internal auditor can reconstruct exactly what rules and what fields were in effect. New runs after the change evaluate against the new state. The common failure where a mid-quarter policy change silently reroutes runs already in approval does not happen because the version is part of the run context.

Does the open API cover inbound triggers and outbound actions?

Yes. The open API covers both directions. Outbound: a flow step calls any HTTP API with retries, idempotency keys, typed request and response payloads, and audit events on every call. Inbound: external systems call signed webhooks that trigger named flows with the webhook payload passed in. The common failure where a vendor markets "integrations" and ships three logos does not happen because the API is the integration layer. Teams integrate with any system that speaks HTTP, which in practice means any system a modern revenue stack touches.

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