AI Conversational Search & Discovery

Answers Buyers Can Trust

Search and discovery experiences tuned for how buyers actually ask questions, with structured content, retrieval, evaluation, and UX patterns reviewed by experienced operators.

Plan a Discovery Project See Search & Discovery Work

When This Fits

When site search and filters don't match natural language needs.

Buyers describe problems, not SKUs. Static search boxes and faceted nav alone miss intent, especially in complex catalogs.

High-consideration queries

Comparisons, compatibility, and sizing need answers tied to source content.

Content isn't AI-ready

FAQs, specs, and policies aren't chunked, tagged, or current.

Hallucination risk

Off-brand or wrong answers erode trust and create liability.

Ops can't maintain another silo

Answers should pull from the CMS and commerce systems you already own.

Measurement is fuzzy

You need to know whether discovery changes conversion, assisted revenue, or support load.

Performance budgets

Assistant UI and retrieval can't tank mobile performance.

Search + Engineering

Discovery backed by real content operations.

We connect editorial workflow, schema, and retrieval so the assistant is part of your stack, not a chat bolt-on.

Established Technical Partner

Two-plus decades shipping web platforms across industries and stacks.

Senior-Led Delivery

Engineering and architecture leads stay on the project after the pitch.

One Accountable Team

Strategy, design, engineering, and support work from the same plan.

How We Deliver

Content audit, retrieval design, UX, evaluation.

We define what “correct” means, instrument citations, and iterate with human review loops.

Intent & corpus review

What questions matter and which documents are authoritative.

Retrieval architecture

Hybrid search, embeddings, and freshness rules.

Experience design

Prompting UI, fallbacks, and escalation to human help.

Eval & rollout

Golden questions, regression tests, and staged release.

Relevant Work

Conversational search and discovery launches.

Search and discovery programs where conversational AI improved product findability and conversion rates.

Furniture Retail - Ecommerce

Today’s Patio: Shopify + STORIS Integration with AI Search & Offline Conversion Tracking

Endertech helped Today’s Patio move from WooCommerce to Shopify, integrate their STORIS ERP, re-architect a complex catalog, and layer on conversational search and offline conversion tracking—creating a scalable ecommerce and marketing foundation that continues to support strong online growth.

View case study

Typical Components

Vector search, LLMs, and your commerce graph.

We integrate with vendors or open models depending on latency, cost, and policy constraints.

Search & vector stores

OpenSearch, Postgres pgvector, or managed retrieval services.

LLM orchestration

Tool use, citations, and guardrails in application code.

Content pipelines

ETL from CMS/PIM with chunking and metadata enrichment.

Frontend patterns

Next.js components, streaming responses, accessibility.

Analytics

Query logs, satisfaction signals, and A/B hooks.

Safety

PII redaction, prompt injection defenses, and audit logs.

Ways to Work Together

From prototype to production assistant.

Validate the idea with a scoped sprint, then scale to a full assistant sized to your catalog complexity and risk tolerance.

Discovery sprint

Answer whether conversational UX moves your metric.

MVP assistant

Scoped corpus, UI, and evaluation harness.

Scale & tune

Latency, cost, and quality improvements post-launch.

Content ops partnership

Ongoing freshness and taxonomy support.

Start With the Problem

Buyers asking questions your search can't answer?

Share the catalog and pain points. We'll propose a discovery approach tied to source content, measurement, and rollout risk.

Plan a Discovery Project See Search & Discovery Work