AI chatbots, LLM apps & RAG
AI assistants that answer from your knowledge, with sources
Navelo Software builds custom AI chatbots and retrieval-augmented generation (RAG) assistants that answer from your own documents, help centre, product data and internal systems. Answers cite their sources, respect each user's permissions and are tested for accuracy before launch, for customers on your website or for staff inside your tools.
At a glance
- Engagement
- Fixed-scope projects or ongoing product teams
- Cadence
- Live demo and working build every week
- Clients
- Startups and businesses worldwide
- You own
- 100% of the code, designs and accounts
Overview
A general-purpose chatbot knows the internet; it does not know your refund policy, your contract terms or last week's product release. Retrieval-augmented generation fixes that by finding the relevant passages in your content and handing them to the model with the question, so answers are grounded and traceable.
Getting this right is mostly data work: cleaning and chunking documents, keeping the index fresh, filtering by who is asking, and measuring whether answers are correct. That is where we spend our time.
What you get
What’s included. End to end.
01
Knowledge ingestion pipeline
Connectors for help centres, PDFs, wikis, drives, databases and websites, with scheduled re-syncs so answers stay current.
02
Retrieval that finds the right passage
Hybrid keyword and semantic search, re-ranking and metadata filters, tuned on your real questions.
03
Answers with citations
Every answer links to the passages it used, and the assistant says when it does not know instead of guessing.
04
Permission-aware access
Users only get answers from content they are allowed to see, enforced at retrieval time.
05
Website, app and team channels
Embeddable web widget, in-app chat, Slack or Microsoft Teams, WhatsApp and email, from one backend.
06
Accuracy testing and analytics
An evaluation set of real questions, answer-quality scoring, unanswered-question reports and human hand-off.
- Retrieval-augmented generation
- Hybrid & semantic search
- Source citations
- Permission-aware retrieval
- Multilingual answers
- Human hand-off
- Web, Slack & WhatsApp
- Answer-quality evaluation
Typical technology
- OpenAI, Anthropic & Google models
- Open-weight models
- PostgreSQL & pgvector
- Vector databases
- Re-ranking models
- TypeScript & Python
- Streaming APIs
Indicative only: we choose the stack per project, around your team, budget and existing systems. See how we work.
What it means for you
01
Faster answers
Customers and staff get a sourced answer in seconds instead of searching or waiting in a queue.
02
Fewer repeat questions
Routine questions are handled automatically, and the hard ones reach a person with context attached.
03
Answers you can audit
Citations and logs show exactly where every answer came from.
Related work
Built by our team. Open the details.
These are Navelo Software concept builds, not client projects: a support assistant that cites the help centre, a voice receptionist and a document-reading agent. Each page shows the screens and the architecture behind it.
ResolvoAI · Customer Support · Web · ConceptAn AI support agent that knows when to ask a human.
ReceptiaAI · Voice Receptionist · Web · ConceptAn AI receptionist that answers, books and knows when to escalate.
DocuviaAI · Document Automation · Web · ConceptAI that reads invoices, checks them and posts them.
Process
How we work. Week by week.
- 1
Content audit
We review your sources, gaps and permissions, and collect the questions people actually ask.
- 2
Retrieval prototype
We index a representative slice and measure how often the right passage is found.
- 3
Assistant build
Conversation design, prompts, citations, hand-off rules and the interface for each channel.
- 4
Evaluate and launch
Accuracy, refusal and latency targets are met on the test set before go-live.
- 5
Improve from usage
Unanswered and low-rated questions feed back into content fixes and retrieval tuning.
Pricing
Every product is different. So is every quote.
We don’t sell packages. We scope ai chatbots & rag development around your goals and send a fixed quote you can plan around.
- Step 1
Tell us about it
A few lines on the product, users and timing.
- Step 2
Scoping call
Goals, must-haves and constraints — a conversation, not a pitch.
- Step 3
Fixed quote
A written scope, timeline and price. Yours to keep.
Why Navelo Software
Why teams choose us.
- We treat retrieval quality as the main job, and measure it.
- Permissions are enforced in retrieval, not left to the prompt.
- Citations and honest 'I don't know' answers by default.
- Model-agnostic, so you can move to a cheaper or private model later.
- You own the index, pipelines, prompts and evaluation data.
FAQ
Common questions.
What is RAG (retrieval-augmented generation)?
RAG is a technique where the system first searches your own content for the passages relevant to a question, then gives those passages to a language model to write the answer. It keeps answers grounded in your data and lets the assistant cite its sources.
Should we use RAG or fine-tune a model?
For most business assistants, RAG comes first: it handles changing information, supports citations and respects permissions. Fine-tuning is better for teaching a consistent style, format or narrow skill. Many production systems use RAG and only add fine-tuning for specific gaps.
Will the chatbot make things up?
Any language model can, which is why we ground answers in retrieved sources, instruct the assistant to decline when the sources don't cover a question, show citations, and test against a set of real questions before launch.
Can the assistant work in several languages?
Yes. Modern models answer well in most major languages, including from source documents written in a different language. We test the languages that matter to you.
How much does an AI chatbot cost?
Every product is different, so we don't publish fixed prices. After a short discovery conversation about your goals, users and must-have features, Navelo Software sends a written scope with a fixed quote and timeline. Get a quote and you'll hear back within one working day.
Do I own the code and designs?
Yes. Everything we create for your project — source code, designs, documentation and accounts — belongs to you and is delivered into repositories and accounts in your name.
Do you work with clients in other countries and time zones?
Yes. Navelo Software works with founders and product teams worldwide. We run projects asynchronously with written updates, shared boards and a weekly live demo scheduled at a time that suits your team.
Related services
- Custom AI agents that use your tools and data to complete multi-step work, with guardrails built in.AI Agent Development
- Open-weight models deployed on your servers or private cloud for data that must stay in-house.Private & Local LLM Deployment
- Process mapping and automation across your tools, combining rules, AI and human approvals.AI Automation & Workflows
Guides from the Journal
- AI Use Cases · 5 minHow to Build an AI Chatbot Trained on Your Own Data
- AI Development · 7 minRAG vs Fine-Tuning: How to Choose for Your AI Product
- AI Tools · 4 minHow to Choose an LLM for Your Business: A Practical Framework
- AI Use Cases · 7 minAI Customer Support Automation: A Playbook That Survives Contact With Customers
- AI Agents · 6 minAI Agents vs AI Workflows vs Chatbots: How to Choose
- AI Automation · 6 minHuman-in-the-Loop AI Workflows: Six Design Patterns for Safe Automation
Work with us
Planning ai chatbots & rag development? Let’s scope it.
Tell us what you're building. We reply within 24 hours, and once the scope is clear you get a written plan, timeline and fixed quote — no obligation.