Customer support assistants
Resolve common questions with policy-grounded answers and reliable escalation.
- Website and app chat
- Ticket creation
- Conversation history
AI Chatbot & RAG Development
AI assistants grounded in your verified knowledge
We build customer and internal assistants that retrieve the right source, cite the answer, respect permissions, and escalate when confidence or policy requires a person.
Governed AI delivery for teams worldwide
Selected brands and delivery experience
Services
What we build with AI Chatbot & RAG Development
Internal knowledge assistants
Help teams find procedures, policies, product detail, and operational knowledge.
- Permission-aware search
- Source citations
- Feedback capture
Lead qualification chatbots
Understand intent, collect useful context, and route qualified enquiries.
- Guided discovery
- CRM sync
- Meeting handoff
Multilingual assistants
Support multiple markets while grounding answers in approved localized sources.
- Language routing
- Local knowledge
- Terminology control
RAG search experiences
Combine semantic retrieval, filters, reranking, and citations for better discovery.
- Hybrid search
- Reranking
- Citation UX
Embedded product assistants
Deliver contextual help and actions inside SaaS, ecommerce, web, and mobile products.
- User context
- Product actions
- Analytics events
Architecture
AI Chatbot & RAG Development architecture for safe production delivery
400+
Projects
3+
Years
20+
Markets
Production-gradeBuilt to scale
01
Content ingestion
Processes approved documents, pages, tickets, and records while preserving useful metadata.
- Source connectors
- Change detection
- Metadata mapping
02
Retrieval pipeline
Uses filters, semantic and keyword retrieval, and reranking to select useful evidence.
- Hybrid search
- Permission filters
- Reranking
03
Grounded generation
Builds an answer from retrieved evidence and follows task-specific response rules.
- Context assembly
- Answer policy
- Citation mapping
04
Conversation experience
Provides clear answers, source links, follow-up questions, and accessible interaction states.
- Streaming responses
- Source display
- Feedback controls
05
Human handoff
Creates a useful escalation with conversation context instead of forcing the user to start again.
- Confidence rules
- Ticket context
- Owner routing
06
Analytics and evaluation
Tracks unanswered questions, retrieval quality, resolution patterns, latency, and cost.
- Question analytics
- Quality evals
- Gap reporting
Process
How we deliver AI Chatbot & RAG Development
A clear, senior-led process from the first strategy call to launch, so every build ships on time and turns into measurable outcomes.
Step 01
Discover and prioritise
Map the workflow, users, data boundaries, failure cost, and the business outcome before selecting any model or platform.
Step 02
Prototype with real inputs
Validate the highest-risk decisions against representative data, edge cases, and human review requirements.
Step 03
Integrate and govern
Connect approved systems with permissions, audit logs, fallbacks, observability, and clear ownership.
Step 04
Launch and improve
Release in controlled stages, monitor quality and cost, then expand only when the workflow proves dependable.
Production AI SystemDesigned to operate,
Designed to operate,
not just demo
Real AI value comes from dependable integration, controlled behaviour, measurable quality, and an operating model your team can own. We prioritise clearer intent flow, faster decision-making, and measurable improvement across high-value pages.
Every experience is engineered on a modern, proven technology stack, so your product stays fast, secure, and easy to scale. From front-end frameworks to databases and DevOps, we pick the right tool for each layer and keep the codebase clean and maintainable.
Clear business objective
Governed data and access
Evaluation before scale
Clean, maintainable code
Mobile-first & responsive
SEO-ready architecture
Secure and scalable by design
AI Chatbot & RAG Development solution blueprints
Outcomes backed by shipping quality and measurable growth
Customer support
Grounded service assistant
Answers product and policy questions, cites the source, and opens a contextual ticket when needed.
Cited answersTicket handoffGap analytics
View projectView project →
Internal knowledge
Employee knowledge assistant
Makes procedures and internal documentation easier to discover without bypassing permissions.
Role-aware accessSource linksFeedback loop
View project →
Sales enablement
Product and proposal assistant
Retrieves approved product, capability, and policy information for faster, consistent responses.
Approved contentFaster discoveryReview ready
Why teams choose Solvinex for AI Chatbot & RAG Development
Performance is non-negotiable
We combine product thinking, engineering, integration, evaluation, and governance in one practical delivery system.
Grounded responses
Evidence first
Grounded responses
Evidence first
Permission-aware retrieval
Access respected
Permission-aware retrieval
Access respected
Reliable escalation
Humans stay reachable
Reliable escalation
Humans stay reachable
Knowledge maintenance
Fresh by design
Knowledge maintenance
Fresh by design
Choose the right engagement
RAG Discovery Sprint
- Knowledge and permission audit
- Retrieval prototype
- Answer evaluation
- Production roadmap
Most Popular
Production Assistant
- Chat experience development
- RAG and integrations
- Human handoff
- Analytics and launch
Knowledge Operations
- Quality monitoring
- Content gap reporting
- Retrieval optimisation
- New source integrations
AI Chatbot & RAG Development FAQs
Retrieval-augmented generation retrieves relevant information from approved sources and gives that evidence to a language model before it answers. This improves grounding and can provide citations, but still requires careful retrieval, evaluation, and fallback design.
