AI Integration

AI Embedded Into Every Business Process

LLMs and agents wired directly into the CRM, telephony, ITSM, and back-office systems you already run — predictive lead scoring, automated workflows, intelligent decision engines, AI fraud detection. Workflows that compound, not demos that don't.

Neural network nodes connecting workflow inputs to AI-driven outputs. INPUT HIDDEN OUTPUT
// Overview

The Approach

Most AI projects fail at the operating model, not the model. A pilot impresses leadership, the team can't scale it past one workflow, the data is never quite clean, and the system goes quietly into a graveyard of POCs. Meanwhile the cost of inaction compounds — every untouched repetitive task is a small annuity paid to inefficiency.

My approach treats AI as integration work. The intelligent layer sits where the operational data already lives — CRM, telephony, ticketing, back-office — and the agents and models earn their place by removing measurable work, not by impressing a demo audience. LLMs do call QA, predictive models score leads against real outcomes, automation closes loops on tickets, and a fraud engine watches the flows that matter.

The result, repeatedly, is 30–60% productivity gain on the targeted workflows, measurable in hours saved per week and conversion uplift per cohort. The AI stops being a project. It starts being part of how the business runs.

// What's Included

Capabilities In Scope

  • LLM-Powered Workflow Agents

    Agents wired into CRM, ticketing, telephony, and back-office. They retire repetitive work — not just suggest it.

  • Predictive Lead Scoring

    Models trained on call and CRM data to rank leads by genuine conversion likelihood — agents work the queue worth working.

  • AI Fraud Detection

    Anomaly detection on transactions, identities, and call flows. Patterns flagged in minutes — investigators get a ranked queue.

  • Decision Engines

    Rule-and-model hybrids that price, approve, route, or escalate — with auditable reasoning and a human-in-the-loop where it matters.

  • Workflow Automation

    PowerShell, Python, and AI APIs orchestrated end-to-end. The boring 70% of every process replaced, the 30% that needs judgement preserved.

  • CRM / ITSM / Voice Integrations

    EspoCRM, Squaretalk, ServiceNow, M365 — meeting the platforms where they live, not migrating around them.

  • Conversational Interfaces

    Internal chatbots and copilots over the documents and systems your team actually uses — grounded in real data, not the open internet.

  • AI Governance & Safety

    Prompt hygiene, eval sets, drift monitoring, and the policy framework that keeps the AI defensible to regulators and the board.

// Process

Engagement Roadmap

  1. 01

    Workflow Discovery

    Inventory the repetitive work. Quantify where time goes, where errors creep in, where decisions are made on partial data.

  2. 02

    Use-Case Selection

    Choose targets where the value is large, the data is workable, and the operational risk is low enough to ship in weeks.

  3. 03

    Data & Eval Sets

    Curate the training and evaluation data. Define the metric the model is actually optimizing against — before anything is trained.

  4. 04

    Build & Integrate

    Wire the model into the CRM, telephony, or ITSM where it lives. Production integration, not a notebook on a laptop.

  5. 05

    Pilot & Measure

    Run alongside the existing workflow long enough to prove the lift in real numbers — not in a benchmark suite.

  6. 06

    Scale & Govern

    Roll out across the estate with monitoring, drift detection, and a governance framework that survives leadership turnover.

// Outcomes

Measurable Impact

Numbers from real engagements in this domain.

  • 0 Productivity Gain

    Average measured uplift across automated workflows in the targeted teams.

  • 0 Lead Conversion Lift

    After predictive scoring re-orders the agent queue against real conversion data.

  • 0 Operational Cost Cut

    Reduction on the workflows AI absorbed — measured by hours saved per week.

  • 0 Calls AI-Scored

    In a single deployment — transcribed, QA-scored, and routed for human review.

// Relevant Tech

Stack & Tooling

  • Python
  • OpenAI
  • Anthropic
  • LangChain
  • PostgreSQL
  • pgvector
  • EspoCRM
  • Squaretalk
  • REST APIs
  • Webhooks
  • PowerShell
  • Docker
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