Why most CRMs stay half-used
A CRM is only as good as the discipline of the people typing into it. Leads sit unassigned, follow-ups get missed, campaigns launch late, and the same customer ends up as three duplicate records. This platform is built the other way round: the system does the typing, the chasing, and the reporting — and asks a human only for the decisions that actually need one.
Everything below follows the same pattern for every module — workflow, automation rule, campaign, connector, form:
stored as data
deterministic runtime
language → definition
before it goes live
every change, versioned
The AI writes and proposes definitions. It never executes freeform — that single constraint is what makes "dynamic" safe with real customer records.
Platform Explainer Video
Auto-playing cinematic walkthrough of one lead's journey through the platform.
AI-Driven CRM
One Platform · Unlimited Automation
Powered by Autonomous AI Agents
New Web Form Submission
THEN Assign Senior Sales Manager
✓ Rule evaluated deterministically — no LLM in the hot path
Copy drafted by AI, sent through pre-approved WhatsApp templates and consent-checked email.
New qualified lead added — pipeline value +$100,000. Sales manager sees it in real time.
THEN Send reminder automatically
IF Still no response
THEN Close lead, notify manager
Opportunity created — $118,000. AI drafted quotation from the product catalogue and last similar deal. Win probability 74%.
Your AI team never sleeps
Agents score, draft and route. Engines execute deterministically.
Reps and managers approve. Nothing ships to a customer unattended.
Architecture at a Glance
AI Orchestrator
Routes every request to the right agent, keeps conversation and case context, and hands execution to the deterministic engines below.
Dynamic Business Engine
Workflow, automation, rule, connector, form, approval, notification and campaign engines — all driven by versioned definitions, not deployments.
Meet Your AI Team
Click a card to see what each agent is responsible for, and what it hands off downstream.
The Eight Dynamic Engines
Every agent's decisions execute through one of these — configured by users, authored by AI, run deterministically.
Automation Rules, Written in Plain English
A rep types the sentence; the AI authors the rule definition; a human approves it once. From then on it just runs.
THEN Assign Senior Sales Manager
THEN Send WhatsApp Greeting
THEN Send Email + SMS + Notify Salesperson
THEN Create Retention Campaign
Every rule is dry-run against the last 90 days of data before activation — showing what would have fired and flagging conflicts with existing rules — so nothing goes live blind.
The AI-Assisted Customer Journey
Live Interactive Demo
Pick an agent from the menu and click through its own scripted story, at your own pace.
Integration Layer
Connectors are configured, not coded — point at an OpenAPI spec, the agent proposes a field mapping, a human confirms it once.
Tech Stack
Frontend
Next.js · React · TypeScript · Tailwind CSS · Framer Motion
Backend
.NET 8 · ASP.NET Core · Semantic Kernel · SignalR
AI
Azure OpenAI · OpenAI · Claude · MCP Servers
Data & Cloud
SQL Server · Redis · Azure · Docker · Kubernetes
Core Design Principles
Definitions, Not Freeform Execution
AI proposes RuleDefinition / WorkflowDefinition rows. A deterministic interpreter runs them — never an eval, never generated code executed live.
Score with ML, Narrate with AI
Churn, health and win-probability come from calibrated gradient-boosted models. The LLM only explains the number — it never invents it.
No Autonomous Send to a Large Audience
Consent lists, quiet hours and frequency caps live in the send pipeline, not a prompt. A human approves the campaign; AI optimizes within it.
Dry-Run Before Activation
Every new rule or workflow simulates against the last 90 days first, showing what would have fired and any conflicts, before it goes live.
Who's Actually Responsible
| Need | Responsible | AI Involved |
|---|---|---|
| Author a new automation rule | Rule Authoring Agent | Azure OpenAI / Semantic Kernel |
| Store the rule definition | RuleDefinition table (SQL Server) | None |
| Execute the rule safely | Deterministic Rule Interpreter | None — guardrails only |
| Draft campaign copy per segment | Campaign Content Agent | Claude / Azure OpenAI |
| Score leads & churn risk (the number) | ML models (Azure ML / Fabric) | Gradient-boosted, not LLM |
| Explain the score in plain language | Narration Layer | Azure OpenAI / Claude |
| Approve discounts & large sends | Human Manager | Assisted by AI |
| Enforce consent, quiet hours, frequency caps | Notification Engine + Runtime Guards | None |
Beyond CRM
The AI orchestrator, dynamic engines and integrations are industry- and domain-independent. Swap the business modules and rules, and the same platform extends outward.