CEI.ai helps retailers move from pilots to production—deploying agentic AI systems that actively optimize demand, pricing, supply chains, and customer experiences.
We don’t deliver dashboards or slideware. We ship working systems that make decisions, take action, and continuously learn inside real retail operations.
Retail leaders are being squeezed from every direction—volatile demand, thinning margins, fragmented omnichannel data, and rising expectations for personalization and speed.
Most retailers have invested heavily in analytics, cloud platforms, and data science. Yet the business still runs on manual decisions, disconnected workflows, and hindsight.
The result: AI initiatives stall at pilot stage while operations remain reactive.
CEI was built to change that.
CEI believes the next era of retail belongs to agentic systems—AI that doesn’t just recommend what could happen, but decides what should happen and executes within defined business guardrails.
Our approach to retail AI is built on three principles:
Agentic Infrastructure
Real‑time data pipelines connected directly to decision and action loops—so insights don’t die in reports.
AI‑Native Delivery
Spec‑to‑code engineering, autonomous testing, and self‑healing operations dramatically reduce time from idea to production.
AI Adoption Strategy
With a combination of workshops, pilot engagements, and roadmaps, you can feel confident that you’ve developed an AI Strategy for your business that will align with your organizational goals, infrastructure, and processes.
Outcome Ownership
Value metrics are embedded directly into production systems, ensuring AI performance is measured where it matters: margin, availability, conversion, and customer lifetime value.
Agentic forecasting models ingest POS, digital behavior, weather, and promotion signals to continuously rebalance inventory. Autonomous recommendations reduce stockouts and excess inventory while improving service levels.
Policy‑aware pricing agents adjust prices and promotions based on elasticity, competitive signals, and margin targets—protecting profitability without eroding brand trust.
Real‑time decision engines drive next‑best actions across channels, delivering consistent personalization at scale and increasing conversion and customer lifetime value.
Predictive agents detect disruptions early and trigger automated responses—rerouting, re‑ordering, or escalation—creating resilient, self‑correcting supply chains.
AI copilots augment planners, merchants, and associates by automating reporting and surfacing prioritized actions—freeing teams to focus on judgment, not data wrangling.
Spec‑to‑Code for Retail
DARTS converts business rules, pricing logic, and operational constraints directly into production‑ready code. Retail teams achieve 5–7× faster delivery using reusable retail patterns.
Retail Proof of Value
A focused 40‑hour sprint using your data to deliver working agentic flows—not demos. You see what runs, what it costs, and how value scales before committing.
AI‑Native Retail Operations
Prism provides observability, drift detection, and policy enforcement for AI in production—turning one‑off retail projects into reliable, managed capabilities.
| dimension | traditional SI | Analytics Boutique | CEI |
|---|---|---|---|
| Speed to Production | Months | Weeks (pilot) | Weeks (live systems) |
| Delivery Model | Bodies & hours | Models & dashboards | Agentic systems |
| Outcome Ownership | Limited | Advisory | Embedded & measurable |
CEI combines enterprise‑grade engineering with AI‑native execution
—so retail leaders can move fast without sacrificing control.
A multi‑brand specialty retailer struggled with chronic stockouts and excess inventory driven by volatile demand and disconnected forecasting tools.
What CEI Delivered
Impact
A national omnichannel retailer faced margin erosion from reactive promotions and inconsistent pricing across channels.
What CEI Delivered
Impact
CEI helps retailers move beyond experimentation to AI systems that run critical parts of the business—safely, transparently, and at speed.
