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Qzentra

Work

Selected systems we’ve engineered.

Case files rather than a portfolio: the problem, the architecture, the decisions, and what was achieved.

02 Engineering range

Engineering range

Each project marked on the layers it worked in, foundation first. Two are data and infrastructure work with no AI in them; that is the point.

Which layers of the system each case file worked in.
Case fileDataInfrastructureAPIsAIAutomationApplication
Multimodal AI Sales Funnelworked in this layernoworked in this layerworked in this layerworked in this layerworked in this layer
AI Website Audit & Outreach Engineworked in this layernoworked in this layerworked in this layerworked in this layerno
5 TB Zero-Downtime MySQL Migrationworked in this layerworked in this layernononono
Enterprise Data Query Architectureworked in this layerworked in this layerworked in this layernonoworked in this layer
Voice AI Systemsworked in this layernoworked in this layerworked in this layerworked in this layerworked in this layer
  • worked in this layer
  • 01Data
  • 02Infrastructure
  • 03APIs
  • 04AI
  • 05Automation
  • 06Application

03 Case files

Case files

Five systems, each entering through one service pillar and reaching into others. The capability case documents a class of system rather than a single client project, and says so.

  1. 01Case fileAI Systems & Automation

    Multimodal AI Sales Funnel

    An end-to-end sales funnel for a crypto-mining hardware enterprise: Instagram and WhatsApp leads qualified, answered from a catalog of 500+ ASIC miners, scored, and handed to sales.

    Verified factAirtable-backed catalog of 500+ ASIC miners

    Multimodal AI Sales Funnel: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data12345678
    1. 1Instagram DMsAPIs
    2. 2Lead qualificationAutomation
    3. 3WhatsAppAPIs
    4. 4Multimodal AI (text, voice notes, images)AI
    5. 5Product knowledge retrievalData
    6. 6Lead scoringAutomation
    7. 7Human sales handoffApplication
    8. 8Automated follow-up or cold-lead archivingAutomation
  2. 02Case fileAI Systems & Automation

    AI Website Audit & Outreach Engine

    An automated pipeline from a list of target URLs to personalized, segmented outreach: crawling, contact extraction, PageSpeed analysis, LLM-written messages, and automated follow-ups.

    Verified factEvery message grounded in a Google PageSpeed audit of the prospect’s site

    AI Website Audit & Outreach Engine: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data1234567
    1. 1Target URLsData
    2. 2Crawling and contact/social extractionData
    3. 3Google PageSpeed APIAPIs
    4. 4Technical analysisAI
    5. 5LLM-generated personalized outreachAI
    6. 6SegmentationAutomation
    7. 7Automated follow-upsAutomation
  3. 03Case fileData Engineering

    5 TB Zero-Downtime MySQL Migration

    A 24/7 production system on legacy MySQL 5.7 with roughly 5 TB of data, moved to a modern MySQL environment by replication with no service interruption at cutover.

    Verified factApproximately 5 TB, zero service interruption at cutover

    5 TB Zero-Downtime MySQL Migration: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data12345
    1. 1Compatibility audit of MySQL 5.7 workloadData
    2. 2Deprecated variable remediationInfrastructure
    3. 3Replica build and synchronizationInfrastructure
    4. 4Replica promotion at cutoverInfrastructure
    5. 5Query modernization with CTEsData
  4. 04Case fileData Engineering

    Enterprise Data Query Architecture

    Query architectures for analytical workloads across data platforms and data lakes, using distributed and embedded engines over Azure Data Lake storage.

    Enterprise Data Query Architecture: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data1234
    1. 1lake storageData
    2. 2query enginesInfrastructure
    3. 3federationAPIs
    4. 4analyticsApplication
  5. 05Capability caseAI Agents & Voice AI

    Voice AI Systems

    Voice systems on real telephony: AI receptionists, inbound support, outbound qualification, appointment booking, and CRM-integrated calling, with transcription, call analysis, and escalation to people.

    Voice AI Systems: route through the six layers.06  Application05  Automation04  AI03  APIs02  Infrastructure01  Data1234567
    1. 1Telephony: inbound or outbound callAPIs
    2. 2Speech recognitionAI
    3. 3LLM conversation logicAI
    4. 4Tools and CRM actionsAutomation
    5. 5Speech synthesisAI
    6. 6Transcription and call analysisData
    7. 7Escalation and human transferApplication

04 Discuss a project

Have a system like one of these, or one that does not exist yet?

Describe the problem and the systems around it. If the answer is a workflow, a pipeline, a migration, an agent, or an application, that is the work we do.