I build operational AI systems —
backends, orchestration workflows,
and analytics infrastructure.
AI systems engineering end to end — FastAPI backends, Azure OpenAI integrations, escalation routing, Power BI/Fabric analytics, and automation pipelines deployed on Azure. Based in Palm Desert, CA.
Case Study
Desert Glow — Live AI Systems Demo Environment
A functional AI systems demo environment built end to end on Azure — AI concierge with escalation scoring, FastAPI backend, PostgreSQL, Power BI/Fabric analytics, and automation infrastructure. Built as a live portfolio proof system and test case for operational AI.
Inconsistent customer acquisition across fragmented marketing channels
Businesses invest across Meta, Instagram, TikTok, Google Ads, Groupon, SEO, and referral campaigns with no centralized intelligence layer. There is no clarity on which channels generate qualified leads, which campaigns convert, which audiences are profitable, or where revenue actually originates. Marketing budgets grow without growing results.
AI-powered campaign intelligence layer continuously monitors every acquisition channel — tracking lead quality by source, measuring booking conversion rates, identifying high-performing campaigns, surfacing profitable audiences, and recommending real-time optimizations across the entire marketing stack.
Consistent inbound demand, real-time channel ROI visibility, and data-driven acquisition replacing disconnected marketing guesswork.
Captured demand leaks before it can convert
Every missed call is a captured lead — demand your marketing budget worked to generate — that immediately starts evaluating competitors. Busy periods, after-hours windows, and response delays create systematic revenue leakage that compounds silently across every growth channel.
Automated demand-capture recovery detects every missed call and delayed inquiry, fires AI-qualified SMS outreach within seconds, and routes high-intent prospects through intelligent follow-up sequences before they convert elsewhere.
Recovered revenue from captured demand that would otherwise convert into competitor bookings.
No visibility into which campaigns actually drive revenue
Most businesses run Meta, TikTok, Google Ads, Groupon, and SEO campaigns with no unified attribution. Spend increases without insight into which channels drive profitable bookings, which audiences convert, or where budget is leaking into low-margin acquisition.
Unified revenue attribution layer connects ad spend, lead source, appointment bookings, and revenue into one Power BI intelligence system — identifying profitable channels, underperforming campaigns, and real-time optimization opportunities across every acquisition source.
Clear campaign ROI, profitable channel identification, and real-time spend optimization replacing disconnected marketing spend.
Growth workflows operate manually and do not scale
Staff spend time on repetitive, high-volume tasks — follow-ups, appointment reminders, re-engagement messaging, content publishing — that limit growth capacity and create inconsistent customer experiences at scale.
AI workflow automation handles lead qualification, appointment reminders, post-visit retention messaging, re-engagement sequences, and escalation pipelines — operating continuously without manual intervention across every customer touchpoint.
Scalable growth operations with staff focused on high-value revenue interactions instead of repetitive manual tasks.
Owners operate without live growth intelligence
Growth decisions get made from delayed reports, disconnected systems, and incomplete data — with no live view of which campaigns are performing, where demand is leaking, what customer acquisition actually costs, or what is driving revenue today.
Live revenue intelligence dashboards surface campaign ROI, lead quality by acquisition source, booking conversion trends, customer acquisition costs, response speed metrics, and operational performance — continuously, across every channel and customer touchpoint.
Real-time growth visibility — faster decisions, clearer campaign trends, and continuous revenue optimization replacing delayed guesswork.
AI Analytics Dashboard
Operational Intelligence — Not Just Reporting
13 interactive dashboard pages built on Power BI and Microsoft Fabric — plus a floating Dashboard Copilot that lets the business owner ask natural-language questions directly against their own data. Customer interactions, bookings, escalations, reviews, AI conversations, SEO performance, and AI search visibility. All measurable. All live. Ask: “Which leads need follow-up today?” and get a grounded answer.
Ask questions directly against your business data. No SQL. No BI training required.
- Answer natural-language questions about any KPI or metric
- Identify leads that need immediate action
- Explain charts and help you interpret the numbers
- Recommend campaign and service optimizations
- Summarize sentiment trends and flag reputation risks
- Guide you through dashboard pages and filters
- Generate executive summaries on demand
- Report SEO rankings and AI search visibility
- Warn on escalations, no-shows, and abandoned leads
This is not a chatbot. This is not a website. This is the full operational intelligence layer of an AI-powered business — customer acquisition, conversion monitoring, escalation operations, revenue visibility, NLP sentiment intelligence, SEO performance, AI search discoverability, and a natural-language Dashboard Copilot grounded in the business’s own data. All measured. All live. All on Microsoft’s enterprise analytics stack.
Interested in operational AI infrastructure?
Let’s talk about backends, orchestration, analytics, and what I’m building.
Let’s Talk ↗What I Build
Systems I Build
Operational AI systems built end to end — FastAPI backends, Azure OpenAI integrations, orchestration workflows, analytics pipelines, and automation infrastructure.
Multi-channel demand generation infrastructure monitoring Instagram, Facebook, TikTok, Google Ads, Groupon, SEO, and referral — with AI-powered lead capture, intent qualification, and channel performance optimization running 24/7.
Unified revenue attribution across Meta, Google, TikTok, Groupon, SEO, and referral — tracking lead quality by source, booking conversion rates, campaign ROI, audience profitability, and spend efficiency in real time.
Real-time intent classification engines that score lead quality, detect buying signals, trigger escalation tiers, and surface conversion opportunities — turning inbound engagement into booked appointments and revenue.
Automated demand-capture recovery detecting unanswered calls and delayed responses, firing AI-qualified outreach within seconds, and routing high-intent prospects through intelligent follow-up before they convert elsewhere.
AI-assisted content generation for Instagram, TikTok, Facebook, and Google — drafting captions, ad copy variations, promotional offers, and retention messaging, with automated campaign scheduling and distribution pipelines.
Power BI dashboards on Microsoft Fabric — Bronze, Silver, Gold medallion architecture — tracking lead volume, campaign ROI, booking rates, customer acquisition costs, revenue by source, and operational performance with live intelligence.
Logic Apps and Power Automate pipelines converting AI signals into growth actions — lead routing, qualification sequences, appointment reminders, review requests, win-back campaigns, and re-engagement operating automatically.
Automated retention systems — post-treatment messaging, win-back sequences for dormant customers, seasonal campaign automation, review generation workflows, and AI-driven reactivation pipelines protecting lifetime revenue.
Continuous business intelligence monitoring response times, demand volume, conversion funnels, campaign performance, and revenue trends — surfacing optimization opportunities and revenue leaks before they compound.
Tools & Technologies
Technical Stack
Process
From strategy to deployment.
Funnel map audit
A discovery session mapping your full acquisition funnel — lead sources, channel performance, conversion gaps, automation opportunities, and revenue leaks across every customer touchpoint.
Proposal
A clear technical scope, implementation strategy, infrastructure plan, and timeline with fixed deliverables — aligned to specific revenue and growth outcomes.
Build & deployment
Systems are built, integrated, tested, and deployed with real operational functionality — demand generation, attribution, automation, and intelligence working end to end.
Optimization & monitoring
Ongoing campaign analytics, workflow optimization, and AI system improvements based on live acquisition data and revenue performance signals.
About
About Abdi Alamir
AI Engineer • Operational AI Systems • Backend Engineering • Analytics
I’m an AI engineer focused on building operational AI systems end to end — FastAPI backends, Azure OpenAI integrations, orchestration workflows, escalation routing, analytics pipelines, and automation infrastructure deployed on Azure.
My background started in analytics and data science, but my work evolved toward production-grade AI engineering — designing systems where AI handles the routing, qualification, and escalation logic while analytics pipelines provide the observability layer.
- FastAPI backend APIs
- Azure OpenAI integrations
- Orchestration workflows
- Escalation routing
- Analytics pipelines
- Power BI / Fabric
- Azure deployment
My flagship demo project, Desert Glow Lab, is a live AI systems environment built on Azure — AI concierge with escalation scoring, FastAPI backend with PostgreSQL, Power BI/Fabric analytics pipeline, and automation infrastructure. It serves as the functional proof system for this entire portfolio.
System Walkthroughs
See the systems in action.
Technical walkthroughs of the operational AI systems, backend architecture, analytics pipelines, and automation infrastructure built for Desert Glow Lab.
Building AI-powered workflows? Let’s connect.
I’m available for AI backend engineering, orchestration workflows, analytics pipeline design, and Azure deployment — whether that’s a full system build or specific infrastructure work.
FastAPI backends • Azure OpenAI • Orchestration • Analytics pipelines