Artificial Intelligence · Build
We build assistants that answer from your approved content, know the limits of what they cover, and hand over to a human with the full conversation intact. The scope is drawn from real ticket and query data, so the assistant absorbs the questions it can genuinely resolve and escalates the rest rather than guessing. We do not position it as a replacement for your support team; it clears the repetitive volume so people handle the cases that need judgement. Quality is measured on resolution and satisfaction before and after launch, not on deflection volume alone.
In short
Conversational AI handles customer and employee questions in chat, with grounded answers and a clean handover to a person. An assistant that hides the route to a human does more harm than good.
Start a conversationWhat we do
We decide which questions the assistant handles using your real ticket and query data rather than a guess at what people ask. This grounds the scope in actual demand and shows where volume genuinely sits. It also sets a clear line beyond which the assistant should escalate rather than improvise.
We answer from approved content with citations, and the assistant refuses rather than guesses when a question falls outside its scope. Grounding and explicit refusal are what keep confident wrong answers out of customer conversations. Users can see the source behind an answer instead of taking it on trust.
We pass the conversation to a person — with its full context — whenever confidence is low or the customer asks for a human. The route to a person is always visible, never buried. Handing over context means the customer does not have to repeat themselves, which is where most bot handovers fail.
We deploy to web, app or messaging channels and measure resolution rate and satisfaction rather than raw interaction volume. Volume flatters; resolution and escalation quality tell you whether the assistant is actually helping. Monitoring continues after launch so regressions are caught quickly.
What you receive
Documented output your teams keep and can act on without us in the room.
When this work helps
How an engagement runs
Understand the workflow, the data available, the constraints, and what a good outcome would look like. We establish the problem precisely enough to judge whether AI is even the right instrument for it.
Review data protection, security, oversight, and feasibility for the specific use cases on the table. We report which cases are worth building, which are better solved another way, and what would have to be true to proceed safely.
Set out the approach, controls, governance, and evaluation measures before build begins. Deciding data boundaries, oversight, and how success will be measured up front keeps them from becoming retrofits.
Support implementation and evaluate performance, error modes, and control effectiveness in use. We measure the system against the criteria agreed at design, and report honestly where it falls short.
Where we work
Fidova advises on AI adoption and AI governance from Delhi, India, and works with organisations internationally, including teams that must satisfy overlapping regimes such as India's data protection law, the EU AI Act, and GDPR.
Engagements run in English, are scheduled around your time zone, and can be delivered remotely end to end, with on-site time planned where a phase genuinely benefits from being in the room.
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Questions
Straight answers to what buyers ask us before an engagement begins.
Enquiries
Your enquiry lands in the same inbox as every other on this site and is read by us. Tell us the requirement and we will reply with a practical next step.
Prefer email? contact@fidovaadvisory.com
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