Custom AI Chatbots for Support, Sales, and Ops

Q: Which models do you use for chatbot responses?

We are model-agnostic, selecting LLMs based on performance, latency, privacy, and cost. Options include hosted LLMs and tuned open-source models with retrieval-augmented generation (RAG).

Q: How do you prevent hallucinations?

We ground answers with your approved documents using RAG, enforce guardrails, and log citations. Low-confidence responses escalate or fallback to safe answers.

Q: Can it hand off to a human agent?

Yes. The chatbot can seamlessly route conversations to your help desk with transcripts, context, and user identifiers.

Q: What about PII and compliance?

We redact sensitive PII, minimize stored data, and enforce environment separation. Our deployment aligns with your SSO, data security, and compliance policies.

Launch a brand-voiced AI chatbot that answers questions, captures leads, and routes tasks. RAG-grounded, secure, and integrated with your CRM/help desk.

24/7 coverage RAG + Guardrails CRM/Help desk integration Analytics & Observability

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Think Artificial chatbot builder showing intents, data sources, escalation rules, and analytics

Preview of the bot builder: intents, data sources, escalation rules, analytics.

Faster responses

Sub-10 second first response time for routine questions across web, chat, and email.

Higher conversion

Qualify leads and book meetings automatically with CRM sync and clean attribution.

Lower ticket volume

Deflect 35–60% of repetitive tickets while keeping complex issues for your agents.

What you get

RAG with your knowledge

We ingest your help center, policy docs, product specs, and internal notes to ground answers. Source citations are included for trust and review.

Guardrails and tone control

Policies, do/don't lists, PII handling, fallbacks, and safe escalation ensure the bot stays on-brand and on-policy.

Deep integrations

Create tickets, update contacts, check order status, and schedule meetings directly in your CRM/help desk.

HubSpot, Salesforce, Zendesk, Intercom, Freshdesk
Calendly, Google Calendar, Slack, Email
Confluence, Notion, Google Drive

Observability and analytics

Intent coverage, handoff rates, CSAT proxies, deflection, and conversion tracking—visible through a simple dashboard.

How we build your chatbot

Step 1

Discovery & success metrics

We document your workflows, data sources, brand voice, and define clear outcomes like deflection or qualified meetings.

Step 2

Design & integration

We configure RAG, intents, tone, and escalation. We connect your CRM/helpdesk and set up analytics and alerts.

Step 3

Pilot & rollout

We launch to a subset of traffic, tune with real conversations, train your team, and scale to all channels.

Result snapshot

A SaaS client cut repetitive tickets by 48% and increased demo bookings by 22% after implementing a ThinkArtificial chatbot across web and in-app.

Read related insights

Before and after chart showing ticket deflection and demo booking lift from chatbot rollout

Ready to reduce tickets and book more demos?

Fixed-bid pilots available. Typical timeline: 2–4 weeks to production.

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Frequently asked questions

Which models do you use for chatbot responses?

We're model-agnostic. We select based on performance, latency, privacy, and cost. Options include hosted LLMs and tuned open-source models with RAG.

How do you prevent hallucinations?

We ground responses with retrieval from your approved sources, enforce guardrails, and log citations. Low-confidence answers escalate or fallback to friendly responses.

Can it hand off to a human agent?

Yes. We route to your help desk with full context, conversation transcript, and user identifiers for seamless takeover.

What about PII and compliance?

We implement PII redaction, data minimization, and environment separation. We'll align with your SSO, access policies, and logging requirements.

Let's design your chatbot

Share your goals and we'll map a low-risk pilot that proves ROI.

Start the conversation