The category of intelligent automation platforms promises AI on top of workflow on top of data. Most enterprise entries deliver the pieces separately and bill for integration consulting. Strkr starts the category from a different direction: begin with the CRM as the system of record, add Strkr AI inside every record (not in a sidebar), add Flows that run on any object event, add an audit log that captures every automated decision, and expose everything over an open API. The result is an intelligent automation platform where the AI, the flows, and the records live in one tenant with one role matrix and one invoice.
The category is defined by six capabilities working together. AI that reads context across the business. Flows that trigger on any object event. A data model that is a system of record, not a staging table. An audit log that captures every automated decision. An open API so nothing is locked in a vendor UI. And permissions that respect the business role structure rather than a per-feature toggle grid. Strkr delivers each one as a first-class capability on one platform.
Strkr AI reads the contact timeline, the deal history, the account relationships, and the flow context. It drafts replies in the voice of the owning rep, summarizes long threads at the top of records, and suggests next actions grounded in the full history. Not a separate chat tool, not a generic prompt layer.
Flows catch deal events, contact events, email events, campaign events, calendar events, Projects events, and custom events the team defines. The flow builder is visual. The flow runtime is retry-safe, rate-budgeted, and audit-logged. Flat seat price with no per-task meter.
The data model is first-class: contacts, companies, deals, products, campaigns, projects, and custom objects with configured schemas. Fields are typed, references are enforced, and the audit log tracks every change. The platform is the system of record, not a replica fed by someone else.
Audit log entries carry the acting flow, the acting user when a flow was edited, the inbound event, the AI prompt where applicable (with content redacted per policy), and the resulting write. A compliance review on automated decisions runs one filter query. The platform is defensible under audit.
Every object has REST endpoints with OpenAPI specs. Webhooks fire on events. Reference flows are editable. The team can export data on demand and migrate out if business requirements change. The platform is portable by design, not by promise.
Workspace roles plus per-entity membership plus manager hierarchy drive what each user sees and can edit. Flows, AI prompts, and audit visibility inherit the matrix. Compliance owners get read access to audit without any admin lift. The matrix is a table, not a scavenger hunt through nested settings.
Enterprise intelligent automation platforms earn their reputation on big slide decks. The engineering reality is worse. The CRM is a stage, the automation layer is a stage, the data lake is a stage, and the AI is a sprinkle. Each stage has its own permissions, its own audit log, and its own licensing. Strkr starts from the opposite assumption: everything on one tenant.
The naive stack is CRM plus iPaaS plus data lake plus AI service plus consulting. Each piece has its own license. Strkr collapses the stack: records live on-platform, flows run on-platform, AI reads the records in-place, and audit covers everything. One license, one tenant, one audit.
A per-task meter looks friendly at 10,000 events a month and ruins the budget at 500,000. Strkr runs flows at the flat seat price with no per-task charge. The invoice is a flat line through growth, not a step function the CFO has to budget around.
The naive AI integration is a sidebar with a chat input. The user copies record context into the prompt and copies the output back. Strkr AI runs inside the record with full context already loaded. Reply drafts, summaries, and next-action suggestions appear where the work is done.
A legacy stack has CRM roles, iPaaS roles, data-lake roles, and AI roles. Nothing lines up. Strkr runs one role matrix across every capability. The sales manager permission grants reads of pipeline deals, flow visibility, AI usage context, and audit entries for those records.
Legacy platforms treat export as a project. Strkr publishes an open API and reference migration flows that run in both directions. The data model is portable by design. Exports are a one-click action with the full audit log attached.
A compliance audit on a CRM-plus-iPaaS-plus-AI stack is a reconciliation across three logs. Strkr writes to one append-only audit log that covers records, flows, AI usage, and admin changes. The compliance answer is a single filter query, not a scavenger hunt.
These capabilities are live, not roadmap. The platform runs them inside the tenant boundary with one audit log and the flat seat price. Enterprise customers can request a security review package that covers the full set in one engagement rather than per-component.
Strkr AI reads the contact timeline, deal history, campaign engagement, and flow context. It drafts replies, summarizes threads, suggests next actions, and generates variants of outreach grounded in the record. Every AI call writes an audit entry with the acting user, the record touched, and the policy version.
Flows catch any object event, run visual logic (branches, loops, HTTP, AI calls, data transforms), and write results back with per-tenant rate budgeting and exponential backoff on 429. Every run writes an audit entry with the inbound event, the branch taken, the outbound writes, and the elapsed time.
The data model carries first-class contacts, companies, deals, products, projects, campaigns, and custom objects. Fields are typed, references are enforced, and the audit log tracks every change. The platform is the system of record for the sales, marketing, and ops data the team runs on.
Every object has REST endpoints documented in OpenAPI. Webhooks fire on configurable events with signed delivery. The specs live on the admin page. Reference flows integrate external systems through the API with retry, rate budgeting, and audit on every outbound call.
Workspace roles plus per-entity membership plus manager hierarchy. The sales manager sees the team pipeline, the compliance officer sees audit, the admin sees the role matrix itself. Flows, AI prompts, and audit visibility inherit the matrix. One table, not a scavenger hunt.
The audit log is append-only, tamper-evident, and covers records, flows, AI usage, and admin changes. Retention is configurable per data type. A compliance review on automated decisions, data access, or admin changes runs a single filter query. The platform is defensible under audit.
Marketing runs on the same tenant: campaigns, segments, forms, landing pages, suppression list, and consent capture. The marketing engagement writes to the same contact record the CRM uses. Flows can trigger on campaign events. Strkr AI reads marketing engagement in deal context.
Strkr Projects runs issues, epics, sprints, releases, and roadmaps on the same tenant. Deals can hand off to Projects for implementation. Projects status round-trips to the deal. One platform for sell plus deliver, with the audit log and role matrix shared.
An intelligent automation platform that runs the full sales, marketing, and ops surface needs a serious compliance posture. Strkr runs HIPAA-compliant with BAA, SOC 2 Type II in progress through 2026-Q4, GDPR and CCPA compliant posture, scoped tokens, KMS encryption, and append-only audit on one tenant.
Strkr is HIPAA compliant with a BAA available on request. The posture covers CRM, Marketing, Flows, Projects, Strkr AI, and audit under one tenant boundary. Healthcare software vendors and healthcare-adjacent teams can run the full platform under one compliance review.
SOC 2 Type II is in progress through 2026-Q4 with the control inventory published to prospective customers under NDA. Access reviews, change management, incident response, and logging are documented. The audit covers every capability on the platform rather than one slice.
A GDPR deletion request cascades across the contact record, the deal history, the campaign engagement, the project involvement, and the audit entries per the retention policy. CCPA posture is the same. The privacy response is one page, not a per-component investigation.
Mail OAuth scopes, calendar scopes, HRIS scopes, and third-party API scopes are least-privilege per use case. The scope list is published on the admin page. Rotation is a one-click action. Scoping cuts the blast radius if a token leaks.
Records, flow configurations, AI prompts, audit entries, and files are stored in KMS-backed encrypted storage. Encryption keys are per-tenant. The platform is encrypted end to end inside the tenant boundary and the audit log carries key-rotation events.
Every webhook that Strkr fires carries an HMAC signature the receiving system verifies before accepting the payload. The signing secret rotates on the admin page. A replay with a tampered body is rejected and logged. Delivery stats include signature verification outcomes.
CRM, Marketing, Flows, Projects, Strkr AI, and audit are live on the flat seat price. One platform, one role matrix, one audit log, open API.
Enterprise platforms stitch CRM, iPaaS, data lake, and AI from different components with per-component licensing and per-task metering. Strkr runs the records, the flows, the AI, and the audit on one tenant with a flat seat price. The team buys one license, runs one audit review, and manages one role matrix. The capabilities overlap on the main dimensions; the integration tax is where Strkr saves cycles.
The flow runtime is event-driven with per-tenant rate budgeting and exponential backoff on 429 responses. A 500,000-event month runs at the flat seat price with no per-task meter. The runtime is retry-safe, idempotent on signed delivery IDs, and audit-logged on every run. Teams with higher sustained throughput can request a reserved-capacity engagement, but the baseline supports mid-market enterprise volumes without a pricing conversation.
Strkr AI reads the record in place with full context already loaded: the contact timeline, deal history, campaign engagement, flow state. It drafts replies, summarizes threads, and suggests next actions grounded in that full picture rather than a prompt the user has to paste. Every AI call writes an audit entry with the acting user, the record touched, and the policy version. The AI is a first-class capability on the records, not a chat tab beside them.
Yes. Strkr publishes REST endpoints with OpenAPI specs and signed webhooks for every object. Reference flows cover common integrations (HRIS, ERP, service desk, data warehouse, identity provider). Outbound calls run through retry, rate budgeting, and audit. The platform integrates through the open API without a credit meter in the middle.
Workspace roles plus per-entity membership plus manager hierarchy drive what each user sees and can edit. The sales manager role grants reads of pipeline deals, flow visibility, AI usage context, and audit entries for those records. The compliance owner gets audit visibility across the tenant. The admin edits the matrix itself. The permission system scales to large teams without a scavenger hunt through nested settings.
Strkr publishes an open API, webhooks, and reference migration flows that run in both directions. Teams can export records, flow definitions, AI prompt policies, and the audit log on demand. The platform is portable by design. Replatforming is a bounded project, not a professional services engagement with a per-component scope. The team is not locked in.
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