Custom conversational AI built into your commerce stack — not bolted on top of it.
For B2B, B2B2C, and enterprise ecommerce teams that need chatbots to actually touch live commerce data.
17 yrs Engineering ecommerce since 2009
500 + Projects delivered across Europe and the US
5.0 Clutch rating across 44+ verified reviews
70 customers NPS
Trusted partnerships
★★★★★ 5.0 · 44+ reviews on Clutch
Mid-market & enterprise · EU & US
The problem
Most ecommerce chatbots lack real data access and can’t act. We build the layer that makes them production-ready.
Can’t see live inventory, contract pricing, or current order state.
Can’t execute real operations — returns, refunds, reorders, approvals.
Deflection stalls, CSAT drops, and the bot becomes another cost line.
Blind to account hierarchies, credit limits, and role permissions.
What we build
We design, build, and integrate the following chatbot types for ecommerce operators. Most enterprise programs combine several of these in a single governed agent.
Deflects the repetitive volume your service team handles every day: order status, shipping windows, returns, exchanges, account access, and product basics. Connected live to your OMS, shipping providers, and help center. Answers are grounded in current data, not a stale FAQ export.
Goes beyond deflection. An action-capable agent that initiates returns, issues refunds within policy, reschedules deliveries, and opens warranty tickets. Every action is scoped, thresholded, and auditable. What the agent can do, for which accounts, up to which limits, is explicit.
Guided selling, spec matching, configurator support, and cross-sell logic grounded in your PIM and search index. Qualifies leads, routes to human teams where needed, and keeps pre-purchase ambiguity from becoming lost revenue.
Past-order lookups, one-click reorders, quote requests, PO handling, approvals, and contract-priced catalogs. Respects account hierarchies, credit limits, and role-level permissions. This is where generic chatbots fail hardest and where our ecommerce depth compounds.
Native-language agents across your target markets, with localized tone, policies, and catalog data. Language coverage is scoped during discovery based on where you operate.
Multi-brand, multi-region, multi-language deployments with SSO, RBAC, data residency, PII redaction, audit logging, and CI/CD-aligned release processes. Designed as a first-class part of your commerce architecture — not as a SaaS widget dropped on the frontend.
Differentiators
Retrieval over your catalog, content, and policies. Confidence thresholds, evaluation harnesses with labeled test sets, and continuous accuracy monitoring in production. No hallucinated SKUs, prices, or terms.
The chatbot executes real actions through your commerce APIs — orders, returns, quotes, account updates. ERP, OMS, PIM, CRM, and service-desk integrations are part of the build, not a later phase.
Account hierarchies, contract pricing, approval workflows, custom catalogs. SSO, RBAC, PII handling, audit trails. The defaults assume enterprise, not DTC.
Human handoff with full conversation context. Clear escalation rules. Action thresholds and audit logs. You can tell exactly what the agent did, for whom, and why.
Integrations
We build chatbots that actually move data across your systems. Integration depth is where most ecommerce chatbot programs succeed or fail.
How we deliver
/01
We map the conversations worth automating first — defined by ticket volume, conversion impact, and integration feasibility.
/02
We specify retrieval sources, action surfaces, integration points, guardrails, and the governance model.
/03
We develop the chatbot, integrate with your commerce and service systems, and stand up the evaluation harness.
/04
Accuracy tests, red-teaming against edge cases, and KPI validation with your team before go-live.
/05
Go live with monitoring in place, then iterate on accuracy, coverage, and outcomes against your success metrics.
8–16 weeks for a first production release of a scoped use case. Enterprise programs with multi-brand, multi-market, or multi-system scope run longer and are phased.
Outcomes we commit to
Specific targets are agreed during discovery, benchmarked against your current baseline.
Lower support cost per order through deflection of repetitive tickets, without degrading CSAT.
Higher self-service resolution rates.
Incremental conversion from better product discovery and fewer decision-point drop-offs.
Stronger B2B account efficiency — reorders, quotes, and workflows handled without human intervention.
Measured accuracy in production, with ongoing regression guards and evaluation runs.
Faster mean time to resolution on the tickets your team keeps — agents escalate cleanly with full context.
Why Elogic Commerce
The integrations are what make a chatbot useful. That’s our core discipline, not an adjacent skill.
ERP, OMS, PIM, CRM, and service platforms aren’t foreign to us — they’re where we work every day.
Account hierarchies, contract pricing, and approval workflows are baseline requirements, not edge cases.
Code reviews, CI/CD, observability, test coverage, and documentation. Your internal tech team will recognize the quality.
We commit to metrics during scoping, measure them in production, and iterate until they move.
FAQ
A support chatbot is primarily informational — it answers questions like order status, shipping windows, and return policy. A service chatbot is action-capable — it initiates returns, issues refunds within defined limits, reschedules deliveries, and opens warranty tickets. Most enterprise programs combine both inside a single governed agent.
Access to your commerce platform, the systems we integrate with (ERP, OMS, PIM, CRM, service desk), your product and policy content, sample tickets or conversations, and defined success metrics. Discovery work turns that into a scoped plan.
Yes. We build chatbots that respect account hierarchies, contract pricing, custom catalogs, credit limits, approval workflows, and PO processes. B2B is one of our strongest areas.
Your product catalog, policies, help content, past tickets, macros, and — where relevant — anonymized conversation logs. We prioritize first-party sources so answers are grounded in your business, not public internet content.
We follow enterprise security practices: SSO, RBAC, PII redaction, encrypted data in transit and at rest, audit logging, and data residency configuration as required. We work within your security review process and documentation standards.
Yes. We build multilingual chatbots with localized tone, policy handling, and catalog data. Language coverage is scoped during discovery based on your markets.
A first production-ready release for a scoped use case typically lands in 8–16 weeks, depending on integration depth, data readiness, and governance requirements. Enterprise programs with multi-brand or multi-market scope run longer and are phased.
Adobe Commerce, Shopify Plus, Salesforce Commerce Cloud, BigCommerce, and commercetools. We’ve delivered complex builds on each and integrate chatbots natively into all of them.
Accuracy is engineered. We ground the chatbot in your data through retrieval, run evaluation harnesses with labeled test sets, monitor production accuracy continuously, and set thresholds for human escalation on low-confidence responses.
The chatbot escalates based on configurable rules: low confidence, sensitive topics, high-value accounts, explicit customer request, or unsupported actions. Full conversation context transfers into Zendesk, Gorgias, Salesforce, HubSpot, or your chosen platform.
Typical outcomes include reduced cost per contact, higher self-service resolution, faster response times, and incremental conversion from guided discovery. We commit to specific KPIs during scoping and measure against them in production.
Both. We build custom AI agents when the requirement demands it, and integrate with platforms like Intercom, Ada, or Zendesk AI when that’s the better fit. The choice is driven by your integration depth, governance needs, and long-term TCO — not vendor preference.
Tell us about your environment, your priorities, and the use cases you want to automate first. We’ll come back with a scoped approach, realistic timelines, and a view on the outcomes you can expect.