Website AI assistants
AI chatbots grounded in your docs, pricing, and case studies that answer buyer questions accurately and route qualified leads to sales.
Agentic web & AI copilot development
Agentic web experiences & AI copilotsbuilt into your product or marketing site
Conalytic designs and builds agentic web experiences—copilots, guided workflows, and task UIs embedded in your SaaS or site—with secure tool use and audit-friendly guardrails.
We integrate with your APIs, Conalytic chat, or your LLM stack so users get grounded answers, approvals, and actions without leaving your product.
Grounded answersRAG + guardrails
Sitemap
robots.txt
Allow: /
Sitemap: …/sitemap.xml
URL inspection passedIndexable
Organic workspace
QueryPosΔ
b2b seo agency#4+6
technical seo audit#7+3
organic growth strategy#2+1
google search console setup#11+9
Live GSC syncPosition ↑ 6
🕷️Crawl
Indexed📈Rank
Pillar: Organic growth
Technical SEO
Content briefs
Internal links
Schema
Sitemap
robots.txt
Allow: /
Sitemap: …/sitemap.xml
URL inspection passedIndexable
Organic workspace
QueryPosΔ
b2b seo agency#4+6
technical seo audit#7+3
organic growth strategy#2+1
google search console setup#11+9
Live GSC syncPosition ↑ 6
🕷️Crawl
Indexed📈Rank
Pillar: Organic growth
Technical SEO
Content briefs
Internal links
Schema
AI experiences built with Claude, OpenAI, Gemini, Vercel AI SDK, LangGraph, and your existing product stack.
HubSpot
Salesforce
Microsoft Dynamics 365
Zoho CRM
Pipedrive
WordPress
Webflow
Shopify
Contentful
Sanity
Strapi
Drupal
HubSpot
Salesforce
Microsoft Dynamics 365
Zoho CRM
Pipedrive
WordPress
Webflow
Shopify
Contentful
Sanity
Strapi
Drupal
What we do
Agentic web development services for copilots and AI-native UX
In-product AI copilots
Copilots inside your SaaS that explain data, draft content, and guide users through complex workflows.
Task UIs & generative UI
Interfaces where AI completes multi-step tasks — forms, reports, configurations — and renders results as usable UI, not just text.
RAG & knowledge pipelines
Retrieval-augmented generation with clean content ingestion, embeddings, and access controls so answers stay accurate and current.
Agent-ready websites
Structured data, MCP endpoints, and early WebMCP tools that let AI agents understand and use your site reliably.
Agentic commerce readiness
Machine-readable product data and checkout readiness for emerging standards like Google's Universal Commerce Protocol and the Agentic Commerce Protocol.
Guardrails & evaluations
Prompt-injection defenses, topic boundaries, human handoff, and automated evals that catch wrong answers before users do.
AI feature analytics
Track conversations, task completion, deflection, and conversions from your AI features in Conalytic.
Why Conalytic for AI experiences
Agentic interfaces users trust—scoped data, clear guardrails, and UX that feels native to your product
Product design, engineering, and analytics in one team
We ship production agent UI with rate limits, logging, and human-in-the-loop patterns so support and security teams stay comfortable as you roll out AI features.
Retrieval from your approved content keeps answers accurate and on-brand, with citations back to the source.
Guardrails, permissions, and human handoff protect users and your brand from wrong or unsafe responses.
We track resolved questions, completed tasks, and conversions — not just conversation counts.
How it works
How we deliver agentic web and copilot experiences
Discover use cases, prototype UX, integrate tools, evaluate quality, launch with runbooks.
- 1Audit & baseline
Define
Prioritize AI use cases by user value and feasibility, and define success metrics.
- 2Prioritized roadmap
Prototype
A working prototype on your real data within weeks, tested with real users.
- 3Ship with owners
Harden
Guardrails, evaluations, security review, and performance tuning for production.
- 4Prove in GA4 & GSC
Launch
Deploy, monitor quality and cost, and improve with usage analytics.
Compliance workspace
GDPR & privacy policyAligned
EU cookie & consentConfigured
Data processing (DPA)Documented
llms.txt & AI crawlersPublished
GDPR · EU · UK ready
Security & privacy
AI agents that respect data boundaries
Role-based access, data residency options, PII handling, and prompt-injection defenses keep your AI features compliant with GDPR and your security policies.
Discuss AI securityAI analytics
Know if your AI features are working
Conversation quality scores, task completion, cost per conversation, and conversion impact — reported in Conalytic next to your other marketing and product data.
Explore AI analyticsGA4 property mapped
Search Console linked
Consent Mode v2
Conversions verified
Tracking QA sent to your team
GA4 · GSC · Ads · CRM events
conalytic.com / SEO workspace
Technical auditLive
Indexable URLs98%
Crawl errors3
Core Web VitalsPass
AI assistants that answer buyers and qualify leads
Grounded answers about your product, pricing, and integrations — with lead capture and handoff to sales in your CRM.
Build a website assistant
conalytic.com / SEO workspace
Pillar: Marketing analytics
GA4 setup
KPI goals
Report templates
AI search
Copilots that help users get value faster
Context-aware AI inside your product that explains, drafts, and acts — reducing support tickets and speeding up activation.
Explore copilots
conalytic.com / SEO workspace
✓ GET /pricing → 200 index,follow
✓ canonical → https://conalytic.com/pricing
→ rendered HTML: 142KB (SSR)
! 2 URLs in “Crawled – not indexed” queue
opacity:0 instances in HTML: 0
Websites AI agents can understand and use
Structured data, MCP servers, and emerging browser standards like WebMCP — adopted at the right pace for your business.
See MCP developmentProof in the data
Agentic web delivery outcomes we commit to
01
0+
AI agents and copilots shipped to production
02
0%
Average support deflection from AI assistants
03
0 weeks
Average time from kickoff to working prototype
FAQ
Agentic web & AI copilot FAQ
Security, integrations, models, and timeline for production copilots.
Which AI models do you build with?
We are model-agnostic and work with Anthropic Claude, OpenAI, Google Gemini, and open-source models, choosing based on quality, cost, and data requirements.
How do you stop AI chatbots from making things up?
We ground answers in your approved content with retrieval, set topic boundaries, show sources, and run automated evaluations before and after launch.
Is our data used to train AI models?
We use enterprise API terms that do not train on your data by default and can add data residency and PII controls.
How long does it take to build an AI copilot?
A working prototype typically takes 3–6 weeks; a production launch with guardrails usually takes 2–3 months.
Do we need WebMCP now?
Not yet for most sites — it is still an early browser standard. We start with structured data and MCP, and prepare WebMCP tools when it matures.
Can the AI assistant connect to our CRM?
Yes. Assistants can create leads, look up accounts, and book meetings in HubSpot, Salesforce, and other systems with proper permissions.
Still have questions? Talk to our team
Ready for the next step?
Add an AI copilot your users will actually use
Scope an agentic web prototype with technical spec, guardrails, and a path to production on your stack.
- Indexation → pipeline
- GSC + GA4 native
- Ship weekly
Non-brand clicks
+32%
Index coverage
94%
Program sync
Roadmap, owners & GA4 events aligned