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On-site AI implementation for EC｜FDE × EC

We embed in your EC operations to
run AI in production.

A team that understands your day-to-day work and data across Amazon, Rakuten, your own store, and more partners with you end to end, from identifying issues to operational design, building AI and automation, system integration, operation, and enablement.

You do not need a concrete development theme in mind. Projects stalled at PoC and integration with existing systems are also welcome topics.

EC-operations firstAI & automation buildSystem integrationProduction operationContinuous improvementIn-house enablement
Start from EC operationsRather than starting from AI, we choose what to build from EC business issues: sales, margin, operating workload, and customer service.
Take it to productionWe go beyond prototypes, designing for data, permissions, existing systems, and day-to-day operation.
Leave the capability in-houseWe put operating rules, evaluation methods, documentation, and improvement practices in place so your team can keep it running.

30 seconds

FORWho it is forSupport for EC businesses whose operations and data have grown complex across multiple channels, ads, products, inventory, orders, and customer service.
WHATWhat we doWe review your EC operations on the ground, select the themes where AI and automation deliver the most, then design, build, and embed them into the work.
HOW FARHow far we goWe do not stop at delivering a system; we support adoption tracking, improvement, operational design, team training, and handover in-house.
1Understand the operations→2Decide what to tackle→3Build with real data→4Improve while in use→5Hand over for in-house operation

Problems

01Can't decide what to automate firstWith so many candidate areas, products, ads, orders, inventory, customer service, it is hard to pick the highest-return themes.
02Stuck between PoC and productionA prototype exists, but it is not connected to real data, existing systems, permissions, or operating rules.
03EC operations and systems are disconnectedData is scattered across marketplaces, your own store, ads, order management, inventory, and customer service, leaving manual work behind.
04Reliant on vendors, no in-house know-howEvery change means another request to a vendor, and your team cannot improve or scale it themselves.
What is FDE

Not just a proposal, not just a delivery. We keep building until results show on the ground.

An FDE understands EC operations, finds the issues, builds the fix, and drives adoption on the ground. At ByThink, EC consultants and engineers share one goal and one implementation backlog, so business issues and system development are never split apart.

AspectSiloed supportFDE × EC
Starting pointA proposal or fixed requirementsOn-the-ground operations and business issues
Theme selectionDecided by the clientPrioritized jointly with the field team
ImplementationMay be handed to a separate vendorThe same team designs and builds
ValidationChecked against deliverables and featuresChecked against real work and outcome metrics
Spec changesHandled as additional requirementsIterated on based on actual usage
End pointProposal and deliveryProduction, adoption, and handover in-house

Outcome

Lighten daily workWe cut routine tasks like aggregation, data entry, checking, classification, and copywriting so staff can spend time on improvement.
Speed up decisionsWe organize data across channels to make anomalies, changes, and room for improvement easier to see.
Speed up executionWe shorten the lead time for analysis, planning, production, updates, and validation to keep the improvement cycle moving.
Leave improvement capability in-houseWe aim for a state where your team understands the system and can operate, adjust, and extend it to other work themselves.
Example outcome metrics (set to each implementation theme)
Work hoursVolume processedUpdate lead timeReport prep timeInquiry response timeCorrections & reworkError countAI adoption rateContinued-use rateTasks scaled out

A team that understands EC operations embeds on the ground and builds.

Use cases

Create & improve product contentFrom your product master and existing content, we draft descriptions, selling points, attributes, and channel-specific copy.
Metrics: work hours／volume processed, etc.
Current work → what we build → outcome metric
Ad & creative analysisWe consolidate ad, sales, and creative performance to surface changes and improvement candidates.
Metrics: work hours／volume processed, etc.
Current work → what we build → outcome metric
Review & VOC analysisWe classify reviews and inquiries and feed them into product improvements, FAQs, product pages, and creative.
Metrics: work hours／volume processed, etc.
Current work → what we build → outcome metric
CRM & promotion supportWe organize customer attributes and purchase history to help plan target segments, messaging, and campaigns.
Metrics: work hours／volume processed, etc.
Current work → what we build → outcome metric

* Feasibility and approach are determined after reviewing your EC channels, systems, APIs, data formats, permissions, and security requirements.

Process

Use it in the field, watch the results, improve every week.

STEP 1
Operations & data assessment

We interview the teams involved and map current workflows, time spent, systems, data, and issues.

Current workflowsIssue listAI & automation candidatesRequired-data map
STEP 2
Theme selection & outcome design

We prioritize by business impact, build difficulty, data readiness, risk, and potential to scale.

Priority listTarget tasksOutcome metricsImplementation roadmap
STEP 3
Prototype build

Using a limited scope and real data, we build something the field team can actually try.

Checks: accuracyusabilitytime savedhuman review scopefield adoption
STEP 4
Production build & integration

We embed it into production, covering existing systems, data, permissions, logs, and approval flows.

STEP 5
Operation & continuous improvement

We review results and field feedback to improve the AI, data, UI, prompts, and workflows.

STEP 6
In-house enablement & scale-out

We hand over operations, evaluation criteria, and documentation, and support rollout to other teams and tasks.

1Observe the work→2Pick priority issues→3Build small→4Use in practice→5Measure outcomes→6Improve & scale out

Team

FDE leadOwns field communication, issue framing, prioritization, and project delivery.
EC consultantFrames the EC-business issues and KPIs across sales, ads, products, promotion, and operations.
AI & automation engineerDesigns and builds AI agents, workflows, automations, and interfaces.
Data & systems engineerHandles data structures, APIs, existing systems, permissions, and the runtime environment.

* We combine the roles each engagement needs. Support format (visits, semi-resident, online, etc.) is [TBC].

Why ByThink

We understand not just AI, but the EC front line.

01
We think from both the business and the daily work

Beyond sales and ads, we frame issues across the daily grind: product registration, inventory, orders, customer service, and reporting.

02
We do not split strategy, operations, and engineering

After framing the issues, the same team carries it through to implementation and operational improvement, no handoff to another firm.

03
We design for multiple channels

We account for work and data scattered across Amazon, Rakuten, your own store, and more, and design for the whole.

04
We aim to reduce outside dependence

We leave operating rules, evaluation methods, design docs, and templates so your team can keep improving it.

Cases

Not cases of AI built, but of EC operations changed.

Metrics, client names, and quotes will be replaced with final content once real cases and publication consent are confirmed. We do not publish invented figures.

ClientAn EC business running multiple channels
ChallengeOrders, product master, bundling rules, and data checks had grown complex
BuildNextEngine rollout, product-master definition, data checks, and system integration
ByThink's roleRequirements, feasibility calls, implementation, operating flows, and manuals
Metrics[TBC]

We include this not as an AI case but as evidence of our ability to embed in EC operations and see implementation and operation through.

Team[TBC]
Before[TBC]
Data used[TBC]
What we built[TBC]
Human review[TBC]
Adoption / response time[To be updated after disclosure review]
Handover approach[TBC]

Published only when a real case is available.

Channels[TBC]
Previous method[TBC]
Data integration[TBC]
Automated scope[TBC]
Human review scope[TBC]
Work hours[To be updated after disclosure review]
Impact on decisions[TBC]

Published only when a real case is available.

Security

Data handlingWe classify confidential, personal, and customer data and define what AI is allowed to use.
Access designWe set which data and functions each department, person, and role can view or run.
Human reviewWe separate tasks that can use AI output directly from those that require human sign-off.
Logging & evaluationWe track usage, outputs, corrections, and errors to keep the system improvable.

* The security scope we can support will be finalized after internal review. [TBC]

How to start

01Assessment & implementation plan
A good fit for
Haven't decided what to automate／Want to sort out priorities／Need a plan for internal approval
Key deliverables
Ops mappingAutomation candidatesPrioritiesOutcome metricsImplementation roadmap
02Theme-by-theme build
A good fit for
The target task is decided／Want to move a PoC or production build forward／Want to connect to existing systems
Key deliverables
RequirementsPrototypeProduction systemSystem integrationOperational design
03Ongoing partnership & enablement
A good fit for
Want to automate multiple tasks over time／Want to build an internal driving team／Want to reduce outside dependence
Key deliverables
Improvement backlogEvaluation methodsOperating manualsTeam trainingScale-out plan

* Pricing, duration, and minimum engagement will be published after review. [TBC]

Fit

Companies FDE-style support fits.

✓When FDE-style support fits
  • What to automate, or the requirements, is not yet fully decided
  • A PoC has not made it to production
  • EC operations span multiple systems
  • The spec needs to improve through real-world use
  • You lack people who understand both EC and AI
  • You ultimately want to operate and improve it in-house
–When another approach may suit better
  • An off-the-shelf SaaS subscription alone solves the problem
  • A one-off build with fully fixed requirements
  • You only want AI training
  • You cannot assign a project owner internally
  • You want to add a tool without changing how the work is done

* If none of these apply, we can suggest other options such as an AI/DX advisory or conventional system development.

FAQ

Frequently asked questions

A role that embeds in EC operations and covers everything from identifying issues to designing, building, operating, improving, and internalizing AI and automation.
The main difference is that we do not stop at strategy or proposals, we build the system used in real operations and see it through to adoption.
Yes. We review your current work, time spent, systems, and data, then start from the highest-impact, most feasible candidates.
We recommend limiting the scope and users, validating with real work and data, then expanding. The formal minimum engagement is [TBC].
We will confirm the available formats, visits, on-site, semi-resident, or online, before finalizing an answer. [TBC]
We review your existing setup, systems, and contracts and identify the missing functions or roles.
We decide after reviewing the data types, the AI services used, storage, contracts, permissions, and security requirements.
They depend on the target work, data needed, integrations, number of users, support model, and enablement scope. After an initial call we present a scope and quote.

Where should AI go in your EC operations? We start by framing the issues on the ground.

You do not need to have decided what to build or which AI to use. We ask about your current EC operations, channels and systems, manual work, data, and internal team, then map the tasks where AI and automation can help and what to tackle next.

TODO (connect before launch): inquiry submission API／auto-reply email／staff notification／CRM integration (phase, topics, source, UTM, etc.)／spam protection／GA4 (hero_cta_click / usecase_consultation_click / form_submit / generate_lead, etc.)