A Chatbot That Represents Your BrandAccurately, Reliably, Around the Clock.
We build AI-powered chatbots that answer from your knowledge base, handle real conversations, and escalate with context — so your team focuses on the work only humans can do.
A chatbot that represents your brand accurately.
We build AI-powered chatbots that answer from your knowledge base, handle real conversations, and escalate with context — so your team focuses on the work only humans can do.
Most bots break. Ours don’t.
A bad chatbot breaks the moment a user does not use the expected words, answers from general internet knowledge — including things that are wrong about your business, products and policies — and traps users in loops with no way out. A Dexsof chatbot answers from your verified knowledge base using retrieval-augmented generation.
Every answer is retrieved from your verified knowledge base — never from general internet knowledge about your business.
When it does not know, it says so — rather than inventing a plausible-sounding response that reads like fact.
It knows what it handles, what it escalates, and exactly how to hand a conversation to a human agent.
The full conversation history is passed on intact, so users never have to repeat themselves to your team.
It works across natural language variation — the way people actually phrase things, not just exact keyword matches.
Every response is grounded in content your team has read, checked and signed off before it goes live.
Answers are only as good as the source.
The knowledge base is the foundation. Before any model is deployed, we audit your existing content, structure it for retrieval, and establish the workflows that keep it current.
How we stop it going off-script.
Every chatbot we build has explicit boundaries, escalation rules, and audit capability — so nothing reaches your customers that you have not accounted for.
The chatbot only engages within a defined domain. Off-topic questions receive a polite redirect — not a hallucinated answer about something it was never designed to handle.
When retrieval confidence falls below a defined level, the chatbot escalates rather than generating a low-confidence answer. It admits uncertainty instead of guessing.
Specific question types — complaints, legal queries, anything requiring human judgement — route to an agent automatically, with full conversation context attached.
The chatbot’s language and personality stay consistent across every response — aligned to your brand voice, not generic AI output.
Every conversation is logged and reviewable, so problems are identified systematically — not discovered when a customer complains about a specific interaction.
Meet your users where they already are.
One chatbot, wired into the channels your customers and colleagues already open every day — and into the support desk behind them.
Handles visitor questions on the spot — before they leave the page or fall back to email.
Reaches users in the app they already communicate in daily, with the same grounded answers.
Internal chatbots for IT helpdesk, HR queries, or knowledge retrieval across your organisation.
CRM portals, mobile apps and e-commerce platforms — wherever your users already work.
Connected to Intercom, Zendesk, Freshdesk or a custom desk, with the full conversation history passed across.
Technologies we work with.
We pick the right tool for the job — here's what our teams reach for across every layer.
OpenAIFrom brief to delivery.
Five stages from use case definition to live monitoring — each one with something you can review, test, or sign off on.
We define exactly what the chatbot should and should not handle. Scope prevents the most common chatbot failure — trying to do everything and doing nothing well.
Your documentation, FAQs, product data, and support history are structured as a knowledge base the chatbot can retrieve from accurately — not just keyword-matched.
Dialogue flows, escalation paths, and failure handling are designed before development. Edge cases are mapped in advance — not discovered by unhappy users after launch.
The chatbot is connected to your existing tools and tested against real customer queries before any user sees it. We simulate adversarial inputs, not just happy paths.
Conversation quality, resolution rate, and escalation triggers are monitored from day one. We review flagged conversations weekly in the first month and deploy improvements on a defined release cycle.
Voices from the people we built for.
Dexsof rebuilt a system we'd been promised twice before. They shipped in eleven weeks what two other teams couldn't in eighteen months — and the code is the cleanest I've reviewed in a decade.
Genuine senior engineers. The kind who say 'we shouldn't build that' before we waste a quarter on the wrong thing.
We came for a 6-week prototype. Three years later they still run our core platform.
The team integrated seamlessly with our in-house engineers and elevated the entire output. We shipped on time and under budget.
The mobile app they built has a 4.8-star rating on the App Store. The UX work alone was worth every dollar.
From discovery to deployment in eight weeks. Dexsof is what a modern dev studio should look like.
We brought Dexsof in mid-project to rescue a failing build. They diagnosed the architecture problems in days, refactored the core, and had us back on track within two weeks — without losing a single feature.
Fast and reliable.
Every deadline hit, every estimate accurate. Working with Dexsof felt like having a co-founder with a full dev team behind them.
They picked up our legacy codebase that three other contractors had given up on, cleaned it up, and shipped three new features in the same sprint — all without touching the production schedule. Impressive discipline from the entire team.
Dexsof flagged two architectural issues that would have cost us six months.
Their design and engineering teams worked as one. The result was a product that looked premium and performed even better under load.
Projects in this space.
Common questions.
Anything not covered here, ask us directly — we answer within 24 hours.
Will it actually resolve queries or just collect information?
Designed correctly, yes — it resolves queries. The key is connecting it to accurate, structured knowledge and defining a clear scope. A chatbot that tries to answer everything answers nothing well.
How do you prevent the chatbot from giving wrong answers?
Retrieval-augmented generation grounds every response in your actual content. We also implement confidence thresholds — when the model is not confident, it escalates to a human rather than guessing. The chatbot only answers from what you have given it.
Can it hand off to a human agent when needed?
Yes — seamless handover with full conversation context is a standard feature. We integrate with Intercom, Zendesk, Freshdesk, and custom support systems. The agent receives everything the chatbot gathered, so the user never has to repeat themselves.
How do you improve the chatbot after launch?
Conversation analytics show you where the chatbot fails. We review flagged conversations weekly in the first month and deploy improvements on a defined release cycle. Improvement is data-driven, not based on guessing what went wrong.
Let’s talk about it.
Tell us what you are building and we will get back to you within 24 hours — with honesty, not a sales pitch.