Architecture
Integration Deep-Dive
The 3D view into how everything connects. The 5 beta products share one data model, one event bus, and one intelligence layer.
Core Pattern
Event-Driven Architecture
Every action triggers a chain of intelligent responses. The transactional outbox pattern ensures no event is ever lost.
Product Action Event Outbox Downstream Consumers
+-----------------+ +----------------+ +-------------------+
| SalesOS | | | | ContentStudio |
| creates lead +---->| event_outbox +---->| generates content|
+-----------------+ | | +-------------------+
| Transactional |
+-----------------+ | guarantee: | +-------------------+
| MI discovers | | write + event | | SalesOS |
| opportunity +---->| in same tx +---->| creates lead |
+-----------------+ | | +-------------------+
| Delivery: |
+-----------------+ | Redis Streams | +-------------------+
| ContentStudio | | with at-least | | Analytics |
| publishes post +---->| -once +---->| tracks metrics |
+-----------------+ +----------------+ +-------------------+
|
v
+------------------------+
| Agent Mesh Bridge |
| Bi-directional routing |
| AIOS <-> Agent Jumbo |
+------------------------+550+ Event-Driven Files
Every product emits typed events. Consumers subscribe to exactly the events they need. No polling, no coupling.
Transactional Outbox
Events are written to the outbox table in the same database transaction as the business data. A separate process delivers them to Redis Streams.
At-Least-Once Delivery
Redis Streams consumer groups with acknowledgment tracking. Failed deliveries retry automatically. Idempotency keys prevent duplicate processing.
Data Movement
Data Flow Map
How data moves through the platform: discovery to management to creation to implementation.
MI discovers SalesOS manages ContentStudio DevFlow builds
+----------+ +------------+ creates +----------+
| Business | | Lead | +------------+ | Solution |
| scanning +---->| enrichment +---->| Brand voice +--->| design |
| AI score | | predictive | | AI content | | code |
| alerts | | scoring | | scheduling | | review |
+-----+----+ +------+-----+ +------+-----+ +-----+----+
| | | |
v v v v
+----------------------------------------------------------+------+
| Shared PostgreSQL (735+ migrations) |
| |
| market_intel.* | sales.* | content.* | architect.* |
| opportunities | leads | templates | sessions |
| analyses | pipeline | campaigns | reviews |
| alerts | emails | analytics | learnings |
+----------------------------------------------------------+------+
| | | |
+--------+--------+--------+---------+--------+------+
| | |
v v v
+------------+ +-----------+ +------------------+
| Redis | | Agent | | Observability |
| Streams | | Mesh | | Prometheus |
| pub/sub | | 62 agents | | Grafana + Loki |
+------------+ +-----------+ +------------------+Scale
API Surface
457 routes, 219 database tables, 62 governed agents — all connected through a unified event bus.
| Product | API Routes | DB Tables | AI Agents |
|---|---|---|---|
| ContentStudio | 87 | 62 | 4 |
| SalesOS | 28 | 18 | 6 |
| Market Intelligence | 24 | 12 | 3 |
| BookingFlow | 42 | 22 | 2 |
| ArchitectFlow | 16 | 8 | 4 |
| DevFlow | 18 | 10 | 4 |
| SwarmOps | 32 | 14 | 12 |
| AIOS Dashboard | 56 | 28 | 8 |
| Other Products | 154 | 45 | 19 |
| Total | 457 | 219 | 62 |
AI Coordination
Agent Mesh
62 governed agents coordinated through Redis Streams with bi-directional task routing.
+---------------------+
| Agent Router |
| Task analysis |
| Skill matching |
| Load balancing |
+---------+-----------+
|
+---------------+---------------+
| | |
+--------v------+ +-----v-------+ +-----v--------+
| Planning | | Execution | | Verification |
| Agents (10) | | Agents (34) | | Agents (18) |
+--------+------+ +------+------+ +------+-------+
| | |
+--------v------+ +------v------+ +------v-------+
| spec-writer | | implementer | | qa-engineer |
| spec-shaper | | devops-eng | | sec-auditor |
| contract- | | content- | | impl-verif |
| designer | | creator | | full-stack |
| product- | | seo-opt | | verifier |
| planner | | email-comp | | perf-tester |
+---------------+ +-------------+ +--------------+
| | |
+-------+-------+-------+-------+
| |
+-------v-------+ +-----v-----------+
| Redis Streams | | Compound |
| Task Queue | | Learning Store |
| Agent Mesh | | Impact scoring |
| Bridge | | Auto-integration|
+---------------+ +-----------------+In Practice
Cross-Product Workflows
Four concrete examples of how data and actions flow across product boundaries without any manual integration.
Lead Discovery to Outreach Campaign to Content Creation
Discovers high-potential business in target market, scores opportunity at 8.5/10
Auto-creates enriched lead record, generates personalized outreach sequence
Generates industry-specific content pieces aligned with the lead's pain points
Tracks engagement, adjusts follow-up timing based on content interaction signals
Tech Alert to Solution Design to Code Review to Deploy
Detects emerging technology trend relevant to client's industry
Creates isolated planning worktree, designs solution architecture with spec
4-agent parallel review: security, performance, architecture, testing analysis
Coordinates implementation agents, manages deployment pipeline
Client Onboard to Strategic Assessment to Content Setup
Provisions client workspace with role-based access and org isolation
6 AI advisors run strategic, financial, technical, and operational assessment
Creates brand voice profile, seeds content calendar from strategic priorities
Sets up expansion tracking and renewal signal monitoring from day one
Usage Analytics to Upsell Detection to Expansion Campaign
Detects high-engagement patterns indicating readiness for additional products
Identifies adjacent market opportunities matching client capabilities
Generates expansion proposal with ROI projections from existing usage data
Creates case study and success narrative from client's actual platform metrics
See the platform in action
A 60-minute discovery call. We will map your current systems to the integration points where you will see the fastest ROI.