SmartDuke builds ai agents for e-commerce and retail — systems that autonomously complete multi-step workflows that previously required human orchestration. Conversational commerce isn't hype anymore — agents are driving GMV in stores that have invested in production-grade AI infrastructure. Our approach: Eval coverage on every loop, observability into every tool call, and explicit guardrails around action surfaces before the agent ever touches production.
The problems
we keep solving.
Conversational commerce isn't hype anymore — agents are driving GMV in stores that have invested in production-grade AI infrastructure.
Product discovery breaks at scale
Beyond a few thousand SKUs, traditional search and filters lose to a conversation that understands intent.
Customer support volume scales with order volume
Returns, sizing, fit, availability — most CX questions are repetitive and well-suited to AI handling with human escalation.
Personalization is broken without context
Email blasts and 'recommended for you' miss the mark when the system doesn't know what the customer is actually trying to accomplish.
Three things we'd build
first.
Concrete starting points for ai agents in e-commerce and retail. We pick the one with the highest leverage and the cleanest measurement story.
- Idea 01
Product-finder agent that asks clarifying questions and recommends across catalog with reasoning
- Idea 02
Review-summary copilot that synthesizes customer feedback into structured pros/cons per SKU
- Idea 03
CX agent that handles 80% of inbound and intelligently escalates the rest with full conversation context
Production-grade,
from day one.
We use planner-executor, ReAct, or supervisor-worker loops depending on the problem shape — and resist multi-agent orchestration when a single-agent loop solves it.
Evals before launch.
Every loop, tool call, and structured output is graded with a frozen test set and an explicit rubric. Failed evals block the deploy.
Telemetry from day one.
Traces, latency budgets, token costs, and error rates wired up before the first user touches the system.
Guardrails as architecture.
Input validation, output verification, escape hatches, and human handoff paths designed in — not bolted on after incidents.
Boring stack on the edges.
Cutting-edge model in the middle. Reliable infrastructure around it. Stability where it earns its place.
- ×Runaway loops on ambiguous inputs
- ×Tool-call failures invisible to standard APM
- ×Context truncation as conversations grow
- ×Hallucinated actions when grounding is weak
Common questions.
01How long does it take to build ai agents for E-commerce?
How long does it take to build ai agents for E-commerce?
Discovery is one week. A working prototype (Spark) is 2–3 weeks. Full production Build for e-commerce and retail typically runs 8–12 weeks depending on data complexity, integrations, and compliance scope. We commit to a precise timeline at quote stage.
02What does pricing for ai agents typically look like?
What does pricing for ai agents typically look like?
Every engagement is scoped to outcomes, not hours. Discovery starts in the low four figures. Spark and Build are priced per project. Embed retainers are monthly. We return a quote within 24 hours of inquiry.
03Can you take over an existing agents project that's stalled?
Can you take over an existing agents project that's stalled?
Yes — it's a common engagement. We review what's there, tell you honestly what stays and what we'd rebuild, then ship it to production. E-commerce engagements often start this way.
04What's different about your approach to ai agents?
What's different about your approach to ai agents?
Eval coverage on every loop, observability into every tool call, and explicit guardrails around action surfaces before the agent ever touches production. We hold the same engineering bar across every engagement, regardless of industry — but the specifics for e-commerce and retail are tuned to your trends and pain points.
Same capability, different industry.
Same industry, different capability.
Have an AI product
that needs to ship?
Tell us where you are — early concept, broken prototype, or scaling something that already works. We'll come back within 24 hours with a take and a quote.