AI Decision Enginefor Commerce
It orchestrates workflows, skills, and memory across every upstream and downstream signal, making commerce decisions beyond human capability.
Why do you need an AI Decision Engine?
Every operation runs on millions of decisions a day, most of them micro, all of them time-sensitive. The engine reasons over each one in context and turns that endless stream into measurable business outcomes.
With an AI Decision Engine, you can
Turn fragmented data into decisions
Scattered signals across your stack become one scored, executable next move.
Decide the next best action
For every customer, account, product, service, or workflow, one at a time, at scale.
Prioritize the goals that matter
Revenue, retention, margin, engagement, service quality, risk, or efficiency.
Choose the right workflow automatically
The engine picks the path that fits the context instead of a fixed rule.
Personalize every dimension
Timing, channel, content, offer, recommendation, or escalation, per entity.
Connect to your existing systems
It layers over your current stack. Nothing gets ripped out or replaced.
Build owned workflows end to end
From signal detection to execution and feedback, the flow is yours.
Learn from every outcome
Results feed back in, so each decision sharpens the next.
An AI Decision Engine is the reasoning layer between business context and business execution.
It doesn't just automate tasks. It decides what should happen next.
Build decision workflows end to end
Connect upstream context, compose workflows over modular skills and shared memory, and activate downstream, all orchestrated by one AI Decision Engine at the center of your stack.
Upstream
Connect every source, event, and system so the engine sees full context before it decides.
Workflows
Assemble multi-step flows the engine runs on its own, sensing, deciding, and acting across systems with no manual handoffs.
Skills
Industry skills you add for domain expertise: the specialized judgment to decide correctly in your field.
Memory
Persistent per-entity memory every decision reads and updates, so the engine compounds learning.
Downstream
Push decisions into the systems and channels that execute them across your operation.
Meet Maestro
The end-to-end AI CRM manager for retailers. Maestro puts the Decision Engine to work, owning the full customer lifecycle, deciding the next best action for every customer, and executing across every channel, autonomously.
Owns the lifecycle
Onboarding, retention, replenishment, and winback, run end to end by a single AI manager.
Decides 1:1
A scored next best action for every customer, recalculated continuously as context changes.
Executes end to end
Launches across email, SMS, push, and on-site, with no manual handoffs between tools or teams.
Learns and compounds
Remembers every outcome per customer and gets sharper with each decision it makes.
Beauty & CosmeticsL'Occitane Elevates Post-Purchase Revenue by 235%
Read the L'Occitane case study
Mom & BabyMumzworld Unlocked 42X ROI with Replenit's AI Decision Engine
Read the Mumzworld case study
WellnessOvabalance Grows Repeat Revenue 340% With Decision Engine
Read the Ovabalance case study
Multicategory RetailIBOOD, From Zero to 6.3% Revenue Share in 54-Day
Read the iBOOD case study
Beauty & CosmeticsFaith In Nature Drives 12.71% Total Revenue With Replenit
Read the Faith In Nature case study
Online GroceryGlosel Increase Marketing Automation Revenue by 53%
Read the Glosel case study
PharmaFarmex Achieves a 12X Conversion Boost With Replenit
Read the Farmex case study
Pet RetailKito Pet Achieves 14X ROI With 1-Day Shopify Integration
Read the Kito Pet case studyAn engine built differently
Most decision engines are thin wrappers bolted onto a single tool. Replenit is engineered end to end, the right model for every decision, on owned infrastructure, with memory that compounds.
The right intelligence for every task
Each part of a decision is routed to the expert or model best suited to solve it. Only the capabilities that decision needs are activated, nothing wasted.
Control over quality and economics
Proprietary decision models, Gemma-based models, and self-hosted fine-tuned LLMs, not a wrapper around someone else's API. Replenit owns reasoning, consistency, and cost per decision.
Proprietary decision models
reasoning · scoring
Gemma-based models
generation
Fine-tuned LLMs
content · copy
Embedding & ranking
retrieval
Agents deployed in parallel
Our swarm engine spins up many specialised agents simultaneously instead of running them one after another, collapsing wall-clock time and slashing cost per task. Concurrency is engineered into the core, and it's the moat that's hardest to copy.
Decisioning at commerce speed
Google TPU infrastructure processes large workflow datasets across many models and skills at once, keeping decisions and personalised content relevant in fast-moving markets.
Decisions with continuity
Every decision builds on enriched memory: what happened, what's happening, what's already been done, and what comes next. When context is missing, agents synthesise it to close the gap.
Most engines are islands
Other decision engines live inside a single tool, spinning micro-decisions that never add up to a result. Replenit connects across your stack and drives every decision toward one business outcome.
Get started
Let's talk about what you'll build with the AI Decision Engine
Book a demo and we'll map it to the stack you already run. Or discover Maestro, Replenit's AI CRM manager for retailers, powered end to end by the AI Decision Engine.