Built for enterprise architects evaluating CRM systems

The CRM system architecture that an enterprise architect can audit without rolling their eyes.

Enterprise architects evaluate CRM systems against security posture, extensibility surface, operational cost, and failure mode behavior. Strkr ships an architecture built on AWS primitives with append-only infrastructure, encrypted tokens, open APIs, and transparent performance characteristics.

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What this audience is actually dealing with

The pains that bring buyers here.

Enterprise architects evaluating CRM systems have a set of concerns that go beyond the feature list. The pain points below are what Strkr onboarding hears when the enterprise architect is the primary technical stakeholder.

The black-box runtime

A SaaS CRM where you cannot explain the failure modes.

Legacy SaaS CRM runtimes are opaque. The team cannot explain why a report ran slow, why an API call throttled, why an integration lagged, or how the system behaves under load. Strkr publishes the architecture decisions: AWS Lambda runtime with multi-tenant warm paths, API Gateway with explicit rate limits, materialized rollups refreshed on schedule or event, and HNSW indexed memory for AI retrieval.

The encryption posture gap

Integration tokens stored in plaintext or in a vendor secrets layer.

Several SaaS CRMs store integration tokens (OAuth refresh tokens, API keys, webhook signing secrets) in their proprietary secrets layer with limited transparency. Strkr stores integration tokens in AWS KMS with envelope encryption and platform credentials in AWS Secrets Manager with role-scoped access. The admin never sees the raw token value after it is written.

The deploy risk window

A vendor release that takes down production.

SaaS CRM releases that touch the production surface create a risk window. A buggy release can degrade pipeline search, workflow execution, or inbound email sync for hours. Strkr runs append-only Pulumi infrastructure (route arrays append-only, deterministic esbuild bundles) which ships new capability without rebuilding or redeploying unrelated runtime surfaces.

The data-model lock-in

A proprietary data model you cannot query directly.

Several CRMs expose only a thin query surface that keeps the underlying data model proprietary. Enterprise architects want direct access for data warehouse pipelines, custom reporting, and regulatory extracts. Strkr exports the full record graph in documented JSON at any tier, publishes a REST and GraphQL API with the full schema, and fires webhooks on every record change for event-driven integrations.

The compliance evidence gap

A vendor who says HIPAA but cannot produce the evidence.

Enterprise compliance teams need audit evidence: controls documents, data flow diagrams, encryption posture statements, audit log retention policies, incident response procedures. Strkr publishes compliance posture (HIPAA with BAA, SOC 2 Type II in progress target 2026-Q4, GDPR, CCPA) and makes pre-close SOC 2 workpapers available on request for enterprise due diligence.

The scale ceiling

An architecture that chokes past 1 million records.

Mid-market SaaS CRMs frequently hit a performance wall around 1 million records or 100 concurrent reps. Reports time out, admin console drags, searches lag. Strkr memory layer uses HNSW indexing for vector search and switches to disk-friendly indexed storage for tenants past 1 million records, which keeps retrieval sub-100-millisecond past multi-million record counts.

The runtime architecture

What runs where and how.

Strkr runs on AWS primitives with explicit choices for runtime, data layer, and infrastructure. The cards below are the architectural decisions and how each one maps to a buyer-facing capability.

AWS Lambda runtime

Multi-tenant warm paths with cold-start ceiling.

The API runs on AWS Lambda in a multi-tenant posture. The warm path hits the most common endpoints inside 100 milliseconds. The cold path (first call on a quiet tenant) adds about 400 milliseconds. For tenants with heavy traffic the warm paths stay warm continuously, which keeps the typical API response under 100 milliseconds. The team sees the cold start on the first interaction of the morning and never again on a typical workday.

API Gateway surface

REST and GraphQL with explicit rate limits.

The REST and GraphQL APIs are served through AWS API Gateway with explicit rate limits (varies by tier, built for real integration volume rather than discouraging usage). The rate limits are published in the API documentation. OAuth 2.0 authentication with per-tenant client credentials or user-scoped tokens.

Postgres data layer

Row-level security with tenant isolation.

The transactional data layer runs on AWS RDS Postgres with row-level security enforcing tenant isolation at the database level, not just at the application layer. Tenant data is logically separate and never crosses on a query, which closes the usual multi-tenant data-leak audit concern.

HNSW indexed memory

Vector search for AI retrieval.

The AI retrieval layer uses HNSW indexing (hierarchical navigable small world) which lands close to 150 times faster lookup than brute-force vector search. The payoff is sub-100-millisecond retrieval on a 1 million record memory, which means the Strkr AI prompt feels instant even on mature tenants.

Disk-friendly storage past scale

SSD-optimized vector search for enterprise tenants.

For tenants past 1 million records the memory layer switches to disk-friendly indexed storage, which keeps the insert and lookup latency flat at enterprise scale. The engineering detail does not matter to the end user. What matters is that search stays fast past the point where retrofit stacks start timing out.

Materialized rollups

Dashboards do not recompute on every load.

Dashboards and reports pull from materialized rollups refreshed on schedule or event trigger. The pipeline board loads in under 400 milliseconds on 50,000-deal pipelines because it reads from a prepared view, not from a live join across six tables. The refresh frequency is tunable per report based on the freshness-versus-load trade-off.

Append-only Pulumi infrastructure

Deploys do not disrupt unrelated runtime surfaces.

The infrastructure (Pulumi route arrays append-only, deterministic esbuild bundles) ships new endpoints without rebuilding or redeploying unrelated Lambdas. The team gets new capability (new flow trigger, new AI prompt, new workflow block) without the full-deploy risk window.

The security architecture

How tokens, credentials, and data are protected.

The security architecture matters as much as the feature list for enterprise architects. The cards below are the security surfaces Strkr ships with by default.

AWS KMS for integration tokens

Envelope encryption with role-scoped keys.

AWS Secrets Manager for credentials

Platform credentials with rotation support.

Platform credentials (API keys, OAuth client secrets, database credentials) live in AWS Secrets Manager with automatic rotation support. The admin never sees the raw credential value after it is written. The audit log captures every credential read, write, and rotation event.

TLS 1.3 everywhere

All traffic encrypted in transit.

All API traffic, webhook delivery, and web application traffic runs on TLS 1.3. Legacy TLS versions are not supported. HSTS is enforced on the primary domain and on tenant subdomains.

Audit log

90-day default retention, tunable per tenant.

The audit log captures every record read, every record write, every email send, every SMS send, every workflow execution, every API call, every token access, and every admin console action. 90-day default retention is tunable per tenant up to the compliance ceiling (bar-rule, HIPAA, SOC 2 requirements).

SSO through Clerk

SAML and OIDC on Scale tier.

Single sign-on with SAML 2.0 and OpenID Connect is live on the Scale tier at $119 per seat per month. The SSO provider configuration (Okta, Azure AD, Google Workspace, OneLogin, PingFederate) runs through the admin console. User provisioning via SCIM is available on the Scale tier.

MFA across all tiers

TOTP plus text verification.

Multi-factor authentication is live across all tiers with TOTP (Google Authenticator, Authy, 1Password) and text-based verification as supported methods. The admin can require MFA for all users or scope it to specific roles. The MFA posture includes enrollment, recovery, and audit log coverage.

Verified Domains

Prove ownership on Scale tier.

Verified Domains are live on the Scale tier. The admin verifies ownership of an email domain, which gates the SSO configuration and the auto-provisioning rules. Verified Domains close the social-login spoof risk that mid-market CRMs sometimes carry.

The integration surface for architects

The extension points you can design around.

An enterprise architect wants to understand the extension surface before signing. The cards below are the integration surfaces Strkr ships, with the expected use case for each.

REST API

Simple resource CRUD and bulk operations.

The REST API covers simple resource operations (CRUD on records, bulk operations, search). Documented in versioned OpenAPI schema. Rate limits built for real integration volume. OAuth 2.0 authentication with per-tenant client credentials or user-scoped tokens. Suited for lightweight integrations and quick scripts.

GraphQL API

Complex graph traversals in one query.

The GraphQL API covers complex graph traversals of the record graph (one query returns an account with all contacts, all deals, all activity, all custom-object references). Documented in versioned GraphQL schema. Suited for user-facing applications and dashboards that need multiple related records in one request.

Webhook spec

Outbound events on every record change.

Every record change (create, update, delete, status transition) fires an outbound webhook with HMAC signature. The receiving system verifies the signature and acts on the event. For event-driven integrations (data warehouse pipelines, Snowflake sync, custom reporting) the webhook surface is the primary interface.

Scheduled CSV export

Daily or weekly to SFTP or S3.

Any report can schedule CSV export to an SFTP destination or an S3 bucket. The export preserves column labels, formatted values, and record references. Suited for data warehouse pipelines that run on a daily or weekly cadence rather than real-time.

Workflow engine as a bridge

HTTP action blocks for custom endpoints.

The workflow engine ships an HTTP action block that calls any custom endpoint with signed payloads. For teams that want workflow-driven custom logic (call a pricing engine, validate against a custom rule, write to a custom destination) the HTTP action block is the extension point.

Native integrations

Gmail, M365, Slack, Teams, Zoom, Salesforce, Shopify, Meta CAPI, Resend.

Native integrations ship for the common surfaces. Each is OAuth-consented at the user level, maintained by Strkr engineering, and shipped with release-note updates when the third-party API changes. Suited for teams that want integration without owning the integration code.

Tenant subdomain

Per-tenant URL with brand on Scale tier.

Each tenant gets a subdomain pattern ({slug}.strkr.io on prod, single-origin on dev) with brand colors, logo, and policy references. The subdomain is tunable per tenant and supports a per-tenant custom domain on the enterprise path for teams needing white-label branding.

Head-to-head

Strkr architecture vs typical SaaS CRM runtime.

The comparison below is Strkr architectural posture versus the common pattern of a mid-market SaaS CRM runtime.

Feature	Strkr	Typical mid-market SaaS CRM runtime
Runtime transparency	AWS Lambda posture published.	Proprietary runtime, opaque.
Integration token encryption	AWS KMS envelope encryption.	Vendor secrets layer.
API transparency	REST and GraphQL, versioned schemas.	REST-only, variable versioning.
Infrastructure deploy risk	Append-only Pulumi routes.	Full-deploy release train.
Memory architecture	HNSW indexed, disk-friendly past 1M.	Variable, often brute-force vector.
Report performance at scale	Materialized rollups, sub-400ms.	Overnight cube refresh.
Data export completeness	Full JSON graph on any tier.	Limited CSV, Enterprise for full.
Webhook coverage	HMAC-signed on every record change.	Partial coverage, Enterprise-gated.
Audit log	90-day default, tunable per tenant.	30-day default, Enterprise for extended.
Customer-managed KMS	Available on enterprise path.	Variable or not supported.

How teams use Strkr

Four architect-driven deployment patterns.

The playbooks below are patterns Strkr onboarding sees across deployments where the enterprise architect is the primary technical stakeholder.

Pattern A

The ERP-connected manufacturing deployment.

A 60-rep manufacturing operation needed bi-directional account and order data flowing between Strkr and NetSuite. The integration ran on Strkr webhooks (outbound on account change) and Strkr REST API (inbound on order write-back). The round-trip latency ran under 2 seconds typically. The integration lived on the customer side via a lightweight Lambda handler, which kept the data model owned, not partner-controlled. Total build time was three engineering weeks.

Pattern B

The data warehouse pipeline into Snowflake.

A 180-rep enterprise SaaS team needed CRM data landing in Snowflake for the analytics team. Strkr webhooks fired on every record change, caught by an AWS SQS queue, and landed in Snowflake via a Snowpipe loader. The pipeline ran at sub-second lag typically. The data engineering team queried CRM data from Snowflake using their existing tooling, which closed the historical gap between CRM and warehouse analytics.

Pattern C

The vertical SaaS build on top of Strkr.

A six-engineer team building a vertical SaaS for independent insurance agencies used Strkr as the record substrate. They modeled policy, claim, agent, and carrier as custom objects, built a dedicated admin console on top of the Strkr REST API, and used Strkr webhooks to fire into their proprietary rate-quote engine. Time to first paying customer on their vertical SaaS was 11 months, which the founder cited as roughly a year faster than their build-from-scratch estimate.

Pattern D

The 300-rep enterprise with customer-managed KMS.

A 300-rep enterprise SaaS team ran a security review that required customer-managed KMS keys for integration tokens. Strkr enterprise path configured the deployment with customer-managed KMS. The audit evidence (controls documents, data flow diagrams, encryption posture statements, pre-close SOC 2 Type II workpapers) landed with the security team. The deployment went live on Strkr Scale tier at $119 per seat with the enterprise security configuration.

Pattern E

The 120-rep team split-stacking with Microsoft.

A 120-rep team ran deep in the Microsoft stack (Entra ID for SSO, Teams for comms, SharePoint for documents, Dynamics for CRM). The team wanted off Dynamics but had to preserve the Microsoft ecosystem integration. Strkr onboarding configured SAML SSO against Entra ID, native Teams integration for channel posts, Outlook bi-directional sync, and SharePoint attachment preservation on migration. The Microsoft stickiness held across the migration. Dynamics decommissioned at month three post cutover.

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Common questions

What buyers in this bucket ask most.

What runtime does Strkr use?

Strkr runs on AWS primitives. The API runs on AWS Lambda in a multi-tenant posture with warm paths hitting typical response times under 100 milliseconds. Cold start on quiet tenants adds about 400 milliseconds. The API is served through AWS API Gateway with explicit rate limits built for real integration volume. The transactional data layer runs on AWS RDS Postgres with row-level security enforcing tenant isolation at the database level. The AI retrieval layer uses HNSW indexing for vector search with disk-friendly indexed storage for tenants past 1 million records. The infrastructure runs on Pulumi with append-only route arrays and deterministic esbuild bundles.

How does Strkr encrypt integration tokens and credentials?

Integration tokens for third-party services (Shopify, Meta CAPI, Resend, webhook signing secrets) live in AWS KMS with envelope encryption. The KMS keys are role-scoped so only the appropriate runtime role can decrypt. Platform credentials (API keys, OAuth client secrets, database credentials) live in AWS Secrets Manager with automatic rotation support. The admin never sees the raw token or credential value after it is written. The audit log captures every token read, token write, and token rotation. For enterprise buyers the KMS keys can be customer-managed (BYOK) through the enterprise path.

What is the Strkr API surface for an enterprise integration?

Three API surfaces cover enterprise integration needs. First, the REST API for simple resource operations (CRUD on records, bulk operations, search) with explicit rate limits built for real integration volume. Second, the GraphQL API for complex graph traversals in a single query (an account with all contacts, all deals, all activity, all custom-object references). Third, the webhook spec with HMAC signing on every record change for event-driven integrations. All three are documented in versioned schemas. Authentication is OAuth 2.0 with per-tenant client credentials or user-scoped tokens.

How does Strkr handle multi-tenant data isolation?

Tenant isolation is enforced at three layers. First, the database layer uses Postgres row-level security with tenant identifier on every record. Tenant data is logically separate and cannot cross on a query. Second, the application layer validates tenant context on every API request against the authenticated user token. Third, the storage layer uses tenant-scoped S3 prefixes for attachments. For enterprise buyers with heightened isolation requirements the enterprise path supports dedicated-tenant deployments with physical isolation at the database and compute layer.

What is the Strkr compliance evidence package for enterprise due diligence?

The compliance evidence package includes the controls documents, data flow diagrams, encryption posture statements, audit log retention policies, incident response procedures, business continuity plan, and pre-close SOC 2 Type II workpapers (SOC 2 Type II is in progress with a target close in 2026-Q4). Strkr publishes the summary posture (HIPAA with BAA available on request, SOC 2 Type II in progress, GDPR, CCPA) on the public site and makes the full evidence package available on request for enterprise due diligence. The HIPAA Business Associate Agreement is a one-page document available on request.

How does Strkr handle data residency for enterprise deployments?

Strkr primary data residency is US (AWS us-east-1 and us-west-2) for the standard tenant posture. For enterprise buyers with specific data residency requirements (EU-only, APAC-only, government cloud) the enterprise path supports region-specific deployments. The data residency choice is documented in the subscription agreement and audited through the audit log for compliance. For teams with strict GDPR data residency requirements the EU-only deployment option maps to a dedicated AWS region.

What is the Strkr deploy posture and change management?

Strkr ships infrastructure as code through Pulumi with append-only route arrays and deterministic esbuild bundles. New capability (new workflow block, new AI prompt, new flow trigger) ships without rebuilding or redeploying unrelated runtime surfaces. The deploy frequency is daily on dev and weekly to multiple-times-per-week on prod. Change management follows standard SaaS release train practices with release notes published to the public changelog. For enterprise buyers the enterprise path supports a notification cadence for upcoming changes that touch the integration surface.

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