We build chat bots that handle thousands of customer interactions at once
— answering FAQs, guiding purchases, and routing complex cases to the right person. Always on, always consistent.
Support queues
become too much.
Bots handle FAQs. Agents focus on complex issues.
Customers drop off
outside working hours.
24/7 availability.
Conversations never stop.
Bots feel robotic
and frustrate users.
Conversational design.
Natural language flows.
Integrations are nowhere
to be found.
CRM, e-commerce, and support tools connected.
Didn’t find what you were looking for? Drop us a line at info@toimi.pro.
We build chatbots across categories: customer support chatbots, sales qualification chatbots, internal knowledge chatbots (particularly valuable given Pasadena's substantial institutional clients with extensive knowledge bases), industry-specific assistants, conversational interfaces embedded in products. With modern LLM capabilities, chatbots have evolved dramatically.
For most Pasadena clients, we build on top of foundation LLMs (GPT-4/GPT-4o from OpenAI, Claude from Anthropic, Gemini from Google) rather than training custom language models from scratch. We build custom value through domain-specific prompting and system instructions, retrieval-augmented generation (RAG) over client-specific content, custom tools and function calling, conversation state management, integration with client business systems.
RAG architectures enable chatbots to answer questions using client-specific content. We build RAG systems with vector database infrastructure (Pinecone, Weaviate, Qdrant, PostgreSQL with pgvector), embedding generation pipelines, chunking strategies for different content types, retrieval tuning, hybrid search combining vector and keyword approaches, citation generation. For Pasadena research-adjacent and engineering clients, RAG over technical documentation is particularly valuable.
Useful chatbots do things, not just answer questions. We integrate with CRMs (logging interactions, creating leads and cases), ticketing systems, internal APIs, calendar systems, enterprise systems specific to client operations.
Chatbot safety is business-critical. We implement system prompt engineering establishing appropriate scope and tone, content moderation for user inputs and AI responses, retrieval grounding reducing hallucination risk, escalation patterns handing off to human agents for sensitive issues, logging and monitoring enabling ongoing quality review, response guardrails.
Yes — voice AI is increasingly practical with modern speech-to-text and text-to-speech capabilities. We build voice applications: phone-based voice assistants, voice-enabled web applications, smart speaker integrations, in-vehicle or embedded voice interfaces.
Chatbot metrics combine usage, quality, and business outcomes. Usage: conversation volume, message counts, session lengths. Quality: response relevance, hallucination rates, user satisfaction ratings, conversation completion rates, escalation rates. Business outcomes: support ticket deflection rates, lead qualification rates, conversion from chatbot interactions, support cost reduction.
