Transformation Playbooks

Three proven lanes to activate AI in your business.

Each starts as a focused pilot and scales on the same architecture, governance, and measurement model. Choose your entry point, deliver quick wins, and grow with confidence.

Lane 01

Generative-AI Integration (Flagship)

Put AI to work inside the business, not just on top of it.

This is your AI-in-the-workflow offering where AI acts as an assistant and automation layer across internal processes.

It is not generic automation; it is task-level intelligence that keeps teams inside the tools they already use.

Copilots deflect repetitive work, document tribal knowledge, and return time for the moves that grow the business.

Sub-offerings

Ops Copilot for internal teams (Support, Operations, Success)
RAG Knowledge Hub ("Docs -> Answers")

Where it hurts now

Wasted internal time, slow responses, and tribal knowledge bottlenecks stall momentum.

What this unlocks

Embedded AI that turns internal chaos into repeatable, measurable efficiency across your workflows and knowledge systems.

Explore the copilot playbook

3-phase scope with measurable KPIs (handle-time ↓, CSAT ↑)

Lane 02

Data & Analytics Modernization (AI-Enabling Backbone)

You can't do AI on bad data.

This is your infrastructure modernization pillar — what you do before and underneath the AI.

It is how you prepare the company's data layer to actually support advanced analytics and copilots.

Modernize platforms and governance so finance, product, and customer data stay trusted, timely, and ready for AI.

Sub-offerings

Data Readiness & AI Roadmap
North-Star Analytics (Finance/RevOps)

Where it hurts now

No single source of truth, broken dashboards, and manual reporting keep decisions slow and second-guessed.

What this unlocks

The clean data and clear metrics foundation every AI initiative relies on — governed models, observability, and executive-ready visibility.

See the modernization playbook

Assess data quality, lineage, latency, gaps; define target architecture + ROI roadmap

Lane 03

AI-Powered Customer Experience & Revenue Systems

"Where AI meets your customers."

This is your external-facing transformation — modernizing how mid-market companies serve, retain, and grow customers.

Build AI-driven support and sales experiences (chat, retrieval, escalation) while transforming internal knowledge into retrieval-based Q&A for deflection, onboarding, and response accuracy.

Build ML-driven recommendation systems that personalize journeys, increase AOV, and drive repeat revenue with adaptive offers.

Focus on containment, conversions, and satisfaction with golden dashboards, alerting, and forecasting models that surface CAC/LTV and pipeline health.

Provide clear metrics and governance by assessing current data quality, lineage, latency, and gaps, then defining target architecture and prioritized AI use cases with ROI analysis.

Triage tickets, summarize calls, draft structured notes, route actions, and surface SOP lookups directly inside the customer workflow.

Three-phase scope with measurable KPIs (handle-time ↓, CSAT ↑) keeps every launch accountable.

Sub-offerings

AI Assist for CX (public-facing)
Personalization/Recommenders (Commerce or Content)

Where it hurts now

Reactive customer service, low containment, and generic user experiences leave revenue on the table.

What this unlocks

Moves CX from scripted to adaptive, data-driven, and self-improving across every channel.

Review the CX playbook

Focus on containment, conversions, satisfaction; aligns CX data, content, and automation