Most chatbots are useless. They loop through the same five canned responses, escalate to a human the moment anything gets specific, and leave your customers more frustrated than they were before. We build AI chatbots that actually answer questions, because they pull from your real data, your real documentation, and your real business logic.
SportHub
Flustr
Armor Up America
Rundivo
RAE HealthFrom support desks to sales funnels—each build connects to your real data, systems, and workflows so answers stay accurate and on-brand.
The most common request and the highest-ROI use case. We build support chatbots that resolve tickets by pulling answers from your help center, product docs, order history, and CRM. They handle the repetitive questions your support team answers fifty times a day, and they escalate the hard ones to a human with full context attached.
Support bots are usually the fastest win: fewer tier-1 tickets, happier customers, and a clear before/after metric.
Internal chatbots for your employees. HR policy questions, IT troubleshooting, onboarding walkthroughs, contract lookups, project status checks. The chatbot connects to your internal systems (Confluence, SharePoint, Slack, Jira, your ERP) and answers questions that used to require pinging three different people or digging through a wiki nobody maintains.
Chatbots that engage website visitors, qualify leads based on criteria you define, collect contact information, and route qualified prospects to your sales team. These work best when they can access your product catalog, pricing rules, and CRM data so the conversation feels specific rather than scripted.
Product recommendation bots, order tracking assistants, returns processors, and sizing helpers. Connected to your inventory, order management system, and customer profiles. Your shoppers get instant answers about stock, shipping, and returns without waiting for an email reply.
Chatbots powered by retrieval-augmented generation that search your documentation, databases, and internal knowledge before answering. Every response includes citations so the user can verify the source. This is the architecture that separates a chatbot that guesses from one that knows.
RAG development services→One chatbot brain, deployed across your website, mobile app, Slack, WhatsApp, Microsoft Teams, and SMS. Consistent answers everywhere, with a shared conversation history so users don’t start over when they switch channels.
We start with your actual support data. What questions do your customers (or employees) ask most often? Where does your current system fail? What percentage of conversations could a bot handle without a human? We answer these questions in the first 1 to 2 weeks and give you a clear recommendation on what to build, what to skip, and what it’ll cost.
Your chatbot is only as good as the data behind it. We collect, clean, and index your documentation, help articles, FAQs, product data, and any other sources the bot needs to draw from. For RAG-based chatbots, this means chunking documents, generating embeddings, and loading them into a vector database. For simpler bots, it means mapping conversation flows and building decision trees.
We build the conversational AI layer: the LLM orchestration, retrieval logic, prompt engineering, response formatting, guardrails, and fallback handling. We also build the integration layer that connects the chatbot to your systems (CRM, helpdesk, e-commerce platform, internal tools) so it can look up orders, check account status, or pull up the right policy document in real time.
We test the chatbot against hundreds of real questions from your support logs, not synthetic test cases. We measure answer accuracy, response time, escalation rate, and how well it handles edge cases like ambiguous questions, off-topic requests, and abusive messages. The bot gets tuned based on what we find.
We deploy to your chosen channels: website widget, mobile app, Slack, Teams, WhatsApp, or wherever your users are. We handle the chatbot integration services side: authentication, user context passing, conversation persistence, and handoff-to-human workflows.
After launch, we track how the chatbot performs in production: resolution rate, user satisfaction, escalation patterns, and topics it struggles with. We use this data to improve the bot over time by updating its knowledge base, refining prompts, and adding new capabilities as your needs change.
| Attract Group chatbots | Typical chatbot builders | |
|---|---|---|
| Knowledge source | Your actual data: docs, databases, help articles, CRM | Generic training data or a limited FAQ list |
| Answer quality | Grounded in your content with source citations | Guesses based on pattern matching |
| System access | Connects to your CRM, helpdesk, ERP, order systems | Standalone, no backend integration |
| Hallucination handling | RAG grounding, confidence scores, fallback to human | Confidently wrong with no guardrails |
| Customization | Full control over behavior, tone, rules, escalation logic | Drag-and-drop templates with limited flexibility |
| Ownership | You own the code and data | Vendor lock-in, per-seat pricing |
| Channels | Website, app, Slack, Teams, WhatsApp, SMS | Usually 1 to 2 channels |
OpenAI (GPT-4, GPT-4o), Anthropic (Claude), Meta (Llama 3), Mistral, Google (Gemini), open-source models
LangChain, LlamaIndex, Pinecone, Weaviate, Qdrant, pgvector, ChromaDB
Custom dialog engines, memory management, context window optimization, multi-turn handling
Web widgets (React, Next.js), iOS (Swift), Android (Kotlin), Slack API, Microsoft Teams, WhatsApp Business API, Twilio
Python, Node.js, PHP/Laravel
Zendesk, Freshdesk, Intercom, Salesforce, HubSpot, Shopify, Jira, Confluence, SharePoint, custom APIs
LangSmith, custom dashboards, conversation analytics, satisfaction tracking
Patient intake bots, appointment scheduling assistants, symptom checkers grounded in clinical guidelines, and post-visit follow-up automation. HIPAA-compliant architecture with audit logging and on-premise deployment options.
Account inquiry bots, transaction dispute assistants, KYC document collection, and financial product advisors. Built with compliance guardrails so the chatbot never gives advice it shouldn’t.
Product finders, order trackers, returns processors, and sizing assistants that connect to your live inventory and customer data. These bots reduce support volume and increase conversion at the same time.
In-app support bots that answer questions about your own product by searching your documentation and changelog. Onboarding assistants that guide new users through setup. Admin helpers that explain features and troubleshoot issues.
Student support bots, course enrollment assistants, and tutoring chatbots that answer questions from course materials. Useful for institutions dealing with high volumes of repetitive student inquiries.
A chatbot needs a backend, integrations with your systems, a deployment pipeline, monitoring dashboards, and a handoff workflow to your human agents. We build the complete system. Other chatbot development companies hand you a model and wish you luck with the integration.
We use retrieval-augmented generation to ground every answer in your actual documentation and business data. The chatbot cites its sources. If the answer isn’t in your data, the bot says "I don’t know" and escalates, instead of making something up.
If your chatbot needs to check order status in Shopify, look up a patient record in your EHR, or pull account data from Salesforce before answering, we build those integrations. Not every chatbot project is a FAQ widget.
No per-seat licensing. No vendor lock-in. The chatbot, the data pipeline, the integration layer: it’s all yours. If you hire an in-house team later, they can maintain and extend what we built.
Not synthetic test cases. We pull hundreds of real customer questions from your support logs and measure how the chatbot handles them before it goes live. You see the resolution rate, the failure points, and the improvement plan before launch.
Simple FAQ chatbot
$8,000 to $20,000
2–4 weeks
Single data source, basic Q&A from your help docs, deployed on one channel (website). Good for validating the concept and handling your top 20 to 30 most common questions.
RAG-powered support chatbot
$30,000 to $80,000
1–3 months
Multiple data sources, retrieval-augmented generation, integrations with your helpdesk and CRM, escalation workflows, deployed across 2 or more channels. This is what most of our clients build.
Enterprise AI chatbot
$80,000 to $200,000+
3–6 months
Multi-department deployment, complex integrations with ERP/CRM/custom systems, role-based access, compliance controls, multi-language support, custom analytics dashboards. This covers internal-facing bots with strict security requirements or customer-facing bots at high scale.
What affects the price: the number of data sources, how many systems the chatbot connects to, the number of deployment channels, compliance requirements, and whether you need real-time data access or can work with periodic syncs.
Tell us what your chatbot needs to handle. We'll give you a straight assessment of what's realistic, what it'll cost, and how fast you can get there.
Tell us what your chatbot needs to handle. We'll respond with an honest assessment and realistic timeline.
