Missed calls turn into lost jobs
A lead that waits often becomes somebody else's booked job.
AI Systems Engineer / Technical Founder
AI Automation Systems for Businesses Losing Time to Manual Operations
I design and build deterministic AI systems that connect to your CRM, phone, email, forms, and internal workflows with validation, logs, fallback rules, and human review where needed.
For service businesses, contractors, logistics teams, and operators with repetitive admin work, slow follow-up, or disconnected systems.
CRM + telephony integration
Human fallback paths
Audit logs and queues
Founder-led engineering
No black-box AI handoff
ops-console.live
Incoming
Missed call
Roof repair inquiry
Caller left no voicemail. Source matched to service area and campaign.
ChannelPhone
Delay00:01:12
OwnerUnassigned
AI validation
Schema OK
Qualification path selected
Ask service type, urgency, address, and preferred callback window.
confidence
0.91
Action
Ready
CRM task created
Lead record, summary, owner alert, and SMS response prepared.
Create lead record
Send text-back
Fallback: human review if low confidence
Event log
deterministic workflow
[webhook.received]
[lead.validated]
[crm.record.created]
[fallback.not_required]
[sms.sent]
[owner.notification.queued]
Operational bottlenecks
Your business probably does not need more tools. It needs the systems you already use to work together.
Most operational bottlenecks are not caused by lack of software. They happen between tools: missed calls, slow replies, duplicate data entry, unassigned follow-ups, messy CRM records, and staff manually moving information from one place to another.
Leads sit in inboxes too long
Forms, emails, and chats lose urgency when nobody owns the first response.
CRM records are incomplete
Bad fields and missing context make follow-up slower and reporting weaker.
Staff copy-pastes between tools
People become the integration layer between email, CRM, spreadsheets, and documents.
Follow-ups depend on memory
Tasks slip when reminders, routing, and ownership are not built into the workflow.
Managers cannot see where work is stuck
Without queues and logs, bottlenecks stay invisible until revenue is already lost.
What I Build
Systems that replace manual work with controlled automation
I build constrained AI systems around specific business workflows. The AI does not randomly run your company. It operates inside rules, tool permissions, validation gates, and human fallback paths.
AI Lead Response Systems
For missed calls, forms, website chats, and inbound messages.
- Capture missed calls and inbound leads instantly
- Start SMS/email follow-up
- Ask qualification questions
- Push structured data into CRM
- Alert humans when needed
CRM + Admin Automation
For businesses where staff manually update records and chase tasks.
- Clean and enrich lead records
- Create tasks and reminders
- Route leads by rules
- Summarize conversations
- Reduce repetitive back-office work
Custom Workflow Orchestration
For multi-step processes across documents, email, CRM, invoicing, and approvals.
- Connect existing tools through APIs
- Generate documents and reports
- Move data across systems
- Add approval checkpoints
- Maintain logs and retry queues
Live Proof
See public proof of work
Built from real operating systems, not AI hype
These are proof-oriented system patterns: business flow, controls, and fallback behavior. They are not presented as client case studies unless the underlying work is documented as one.
Lead capture infrastructure
SYS
Missed-Call Text-Back System
Missed call -> webhook -> SMS response -> lead record -> owner notification
- Twilio-style telephony integration
- CRM-ready lead capture
- Designed for contractor/service business workflows
- Fallback if automation cannot classify intent
Autonomous intake workflow
SYS
CRM Lead Qualifier
Inbound lead -> AI qualification -> structured fields -> CRM task -> human review
- Constrained questions
- Field validation
- No silent critical updates
- Reviewable lead summary
Back-office automation
SYS
Ops Orchestration Pipeline
Form/document input -> extracted terms -> generated output -> approval -> email/send
- Approval gates
- Deterministic templates
- Retry queues
- Logs for each step
Sales support system
SYS
AI Dialer Copilot
Live call context -> knowledge retrieval -> objection suggestion -> CRM note
- Retrieval-based suggestions
- Fast operator support
- Does not replace caller judgment
- Useful for sales teams
Deterministic AI
How I stop AI from breaking your operations
AI is useful only when it is boxed into a controlled system. Every workflow I build has explicit tool permissions, validation, logging, retry behavior, and human fallback paths.
1
Input
Call, form, email, chat, document, or webhook.
2
Rules
Business logic, permissions, routing, and edge cases.
3
AI step
Constrained classification, extraction, drafting, or summary.
4
Validation
Schemas, required fields, confidence thresholds, and checks.
5
Tool call
CRM update, SMS, task, email, document, or queue job.
6
Log
Every step becomes inspectable operational history.
Human fallback path
If confidence, rules, or validation fail, the system routes work to a person instead of making a silent critical update.
Tool permissions
The agent can only call approved actions.
Structured outputs
Data must match expected schemas before it touches your CRM.
Confidence thresholds
Low-confidence decisions are routed to a human.
Audit logs
Each step is recorded so failures can be inspected.
Retry queues
Temporary API failures do not silently drop work.
Human override
Critical actions can require approval before execution.
ROI Estimate
Estimate the cost of manual follow-up
Use rough numbers from your business. The goal is to identify whether lead response, CRM cleanup, or workflow orchestration is the highest-leverage first build.
Monthly revenue leakage
Annual revenue leakage
Monthly admin labor cost
Suggested priority
This is a directional estimate, not a financial guarantee.
Process
From messy workflow to working automation
01
Workflow Audit
We identify the manual handoffs, broken data flow, and highest-cost bottlenecks.
02
System Map
I map the current tools, APIs, users, edge cases, and fallback paths.
03
Prototype
A narrow working version proves the automation before expanding scope.
04
Integration
The system connects to your CRM, email, phone, forms, calendar, or internal tools.
05
Validation + Fallbacks
Schemas, logs, confidence thresholds, human review, and retry behavior are added.
06
Launch + Monitor
The workflow goes live with monitoring, improvements, and optional maintenance.
Founder-led Engineering
Founder-led engineering, not agency handoff
You work directly with the person designing the architecture and building the system. I do not sell a vague AI strategy and hand the work to a random junior team. The value is in understanding the workflow deeply enough to automate it without creating operational risk.
Full-stack product engineering background
CRM, telephony, workflow automation, dashboards, and AI agent experience
Builds internal product infrastructure, not only client websites
Practical focus: logs, queues, APIs, fallbacks, and maintainability
SF
Shahzad Farooq
Founder / AI Systems Engineer
system_focus: lead_capture, crm_automation, workflow_orchestration, audit_logs, queues, api_integrations, human_fallbacks
Fit
Good fit / bad fit
Most serious builds require a real implementation budget. If you only need a simple website or tiny chatbot, this is probably not the right engagement.
Good fit
- + You have repetitive operational work happening every week
- + You already use a CRM, spreadsheet, inbox, phone system, or internal tool
- + Missed leads or slow follow-up cost real money
- + You want automation with visibility and control
- + You have budget for a serious implementation
Bad fit
- - You want a cheap chatbot widget only
- - You have no clear workflow or data source
- - You want AI to make high-risk decisions without human review
- - You are not willing to document your process
- - You want a generic website redesign instead of operations automation
Implementation Stack
Tech I build with
The stack depends on the workflow. The principle does not: stable APIs, validated data, background jobs, logs, and clear failure handling.
Laravel
React / TypeScript
Node.js
PostgreSQL / MySQL
Redis / queues
Twilio
OpenAI / LLM APIs
Flowise / n8n
Docker
APIs / webhooks
CRMs / custom integrations
Video Placeholder
2-minute system walkthrough
A real demo URL is not configured yet. This placeholder keeps the page honest while giving the section a clear home for a Loom, Tella, or hosted video later.
2-minute system walkthrough
Next Step
Have a workflow that is costing you time, leads, or visibility?
Apply for an AI Operations Audit. I will review your workflow, tools, bottlenecks, and automation opportunity. If there is no strong business case, I will say that directly.
No generic AI pitch. No black-box automation. We start with the workflow.