Three autonomous AI employees for Polish SMBs: Marcin (lead qualification via SMS), Irena (document OCR + categorisation + routing), Przemek (voice-to-CEO-briefing). Each is an independent Nexus pipeline with ChameleonV2 forms, deltaPrism storage, and configurable RBAC gates.
Version UC2-ENDO-v2.0Date 2026-05-03Owner Uued Viljapuuaiad / Pryzmat MediaStatus Pipeline Defined -- Demo QueuedAuthority Tier 4
Section 01 -- Overview [M]
Field
Value
Use Case ID
UC2
Client Reference [M]
ENDO AI by Pryzmat Media (endo.pryzmat.media) -- Polish SMB AI automation product
System Name [M]
ENDO AI Three Pipelines
Domain [M]
AI Automation / Lead Management / Document Processing / Executive Briefing
One-Line Description [M]
Three independently switchable AI employee pipelines (Lead Qualification, Document Lifecycle, CEO Briefing) deployed as a single Nexus org
Status [M]
Pipeline defined -- Demo queued
Target Delivery [M]
Q3 2026 (demo-complete)
Summary [M]
The Problem: Polish SMBs spend 20-40% of staff time on repetitive intake and routing tasks: qualifying leads from incoming SMS/calls, sorting and categorising received documents, summarising voice memos for executive review. These tasks are manual, error-prone, and do not produce audit trails or structured data for analysis.
The Nexus Solution: ENDO AI positions these tasks as autonomous AI employees. Each "employee" is a Nexus pipeline definition + ChameleonV2 form schema + deltaPrism entity class. The client operates three pipelines independently from a single Nexus instance, switching between them via the pipeline profile switcher. Marcin qualifies SMS leads and books appointments. Irena OCRs documents and routes them to the correct department. Przemek transcribes voice notes and produces structured CEO briefings with action items.
Org Structure [D]
D-06 Resolved: Single Nexus org for ENDO (Pryzmat Media). All 3 pipelines within one org. Demo seeder creates 1 org + 5 RBAC users (Admin, Operator, Reviewer, CEO, System). Pipeline profile switcher demonstrates multi-pipeline capability directly on the canvas.
Section 02 -- Actors [M]
Role [M]
Description [M]
Pipelines [D]
Access Level [D]
Admin
ENDO system administrator. Configures pipeline thresholds, RBAC, and integration endpoints.
All three
Full config access, user management, pipeline enable/disable
Operator
Day-to-day staff. Uploads documents (Irena), records voice notes (Przemek), views lead list (Marcin).
All three
Upload forms, read-only lead list, voice note submission
Reviewer
Resolves low-confidence document classification in Irena pipeline.
Approves and optionally edits briefings in Przemek pipeline.
Przemek only
CEO ChameleonV2 form: approve/revise briefing + edit action items
System (Automated Nodes)
SMS polling, OCR, AI transform, scheduling, forwarding nodes. No user-facing forms.
All three
Pipeline-internal only
Section 03 -- User Stories [M/D]
Pipeline: Marcin (Lead Qualification)
P1 [M]: As the System, I poll the SMS gateway inbox and create a lead entity for each new inbound message so no lead is missed
P1 [M]: As the System, I auto-qualify each lead against threshold rules (budget >= 5000 PLN, need in scope, not blacklisted) and route to appointment scheduling or polite decline
P2 [D]: As an Operator, I view the qualified lead list with scores, appointment links, and reply status so I have full visibility
P2 [D]: As Admin, I override lead qualification (re-qualify a declined lead) when business context requires it
Pipeline: Irena (Document Lifecycle)
P1 [M]: As an Operator, I upload a document via ChameleonV2 form so Irena processes it automatically
P1 [M]: As the System, I OCR the document, classify its type (Invoice/Contract/Certificate/Correspondence), and route to the correct department mailbox
P1 [M]: As a Reviewer, when OCR confidence is low, I see the document thumbnail, category suggestion, and confidence score, and I confirm or override the classification
P2 [D]: As a Compliance user, I view the full document processing audit trail per entity in deltaPrism
Pipeline: Przemek (CEO Briefing)
P1 [M]: As an Operator, I upload a voice note (mp3/m4a/wav) so Przemek transcribes and summarises it
P1 [M]: As the System, I transcribe the voice note (Whisper STT), then AI-transform it into a structured CEO briefing (3-sentence summary, action items with owners and deadlines, key decisions)
P1 [M]: As CEO, I receive the briefing form, review/edit action items, and approve for distribution to team
P2 [D]: As a team member, I receive my assigned action items via email with deadline and link to full briefing
Section 04 -- System Flows [M/D]
Flow A: Marcin -- Lead Qualification (6 Steps) [M]
Qualification result + appointment details (if qualified)
SMS sent: confirmation with link OR polite decline
--
6
Store SmsLead (deltaPrism)
System
All lead fields + score + result + appointment_id + reply_timestamp
SmsLead entity persisted with run_id
--
Result [M]: Lead fully processed: qualified + appointment booked + confirmation sent, OR declined + polite SMS sent. All data stored in deltaPrism. Fully autonomous -- no human gate.
Flow B: Irena -- Document Lifecycle (6 Steps) [M]
Trigger [M]: Operator uploads document via ChameleonV2 Document Upload form.
Email sent to category mailbox (invoices: accounting@, contracts: legal@, certificates: hr@)
--
Result [M]: Document classified, stored with full OCR data, and forwarded to correct department. Low-confidence documents reviewed by human before routing.
CEO decision: Approve and Send / Request Revision + edits
HUMAN GATE -- pipeline pauses until CEO approves
5
Store CEOBriefing (deltaPrism)
System
Approved briefing with CEO edits, approval timestamp, CEO user ID
CEOBriefing entity persisted
--
6
Action Item Distribution
System
action_items[] with owner_role mappings
Email per action item to mapped team member. BCC to CEO.
--
Result [M]: Voice note transcribed, AI-structured into briefing, CEO-approved, action items distributed to team. Full audit trail in deltaPrism.
D-05 Resolved: Real Claude API key for AI Transform node. Produces genuinely useful summaries. API key stored in pipeline config (encrypted at rest). Both Przemek and ARC pipelines share the same AI Transform node implementation.
Section 05 -- Data Model [M/D]
Entities
Entity [M]
Pipeline [D]
Description [M]
Key Fields [M]
States [D]
SmsLead
Marcin
Inbound SMS lead with qualification data
lead_id (UUID PK), from_number, name, company, need, budget, qualification_score, result (qualified/declined), appointment_id, appointment_datetime, reply_sent_at, run_id
RESOLVED 2026-04-18: Real Claude API key. Produces genuinely useful summaries. Encrypted at rest. Shared between Przemek and ARC pipelines.
D-06
ENDO Org Structure
RESOLVED 2026-04-18: Single Nexus org (Pryzmat Media). All 3 pipelines in one org. 5 RBAC users seeded. Pipeline profile switcher for multi-pipeline demo.
D-08
Mock SMS/Calendar Nodes
RESOLVED: Mock webhook trigger (manual POST). Mock SMS send (log + display). Mock calendar (return fake slot). No real Twilio/Google Calendar required for demo.
Section 13 -- Cooperator Brief [D]
Field
Value
Scope [D]
Three independent AI employee pipelines in one Nexus org: Marcin (6-step SMS lead qualification + appointment booking), Irena (6-step document OCR + categorisation + routing with optional Reviewer gate), Przemek (6-step voice transcription + AI briefing + CEO approval + action item distribution).
Stack [D]
Nexus pipeline engine (Python), ChameleonV2 forms (6 variants), Atlas OCR, deltaPrism (4 entity classes), Whisper STT, Claude AI Transform, Mock SMS/Calendar/Email nodes.