Artificial Intelligence · Build
We turn unstructured text — tickets, emails, contracts, reviews, notes — into structured fields your systems and reports can use reliably. The work begins with a precise taxonomy and labelled examples, because vague categories produce vague results no model can fix. We measure accuracy per category rather than in aggregate, since one weak category can be hidden by strong ones, and we route low-confidence cases to a person rather than pretending to full automation. Where modern general models handle the task well with good prompting, we use them rather than training a model you then have to maintain.
In short
Natural language processing extracts structure and meaning from text: classification, entity extraction, sentiment and routing. Its value depends on a precise taxonomy and honest per-category accuracy, not on the model alone.
Start a conversationWhat we do
We define categories and entities precisely, with labelled examples and agreement checks between reviewers. If two trained people cannot agree on a label, no model will do better, so we resolve that ambiguity first. A clear taxonomy is the foundation everything downstream depends on.
We build the models or prompts that produce the structured fields you need, each with a confidence score attached. Confidence is what lets the system automate the clear cases and escalate the uncertain ones. The output is designed to flow directly into your systems rather than to be re-keyed.
We handle the languages, abbreviations and internal terminology your text actually contains, not an idealised version of it. Domain jargon and mixed-language content are where off-the-shelf tools quietly fail. We test against your real text so the system copes with how your people and customers genuinely write.
We measure performance per category and route low-confidence cases to a human rather than forcing a decision. Reporting accuracy by category exposes the weak spots that an overall figure would mask. The review path also generates corrections that improve the system over time.
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.
Related services
Computer vision extracts information from images and video: detection, classification, measurement and inspection. Whether it works at all is usually decided by the capture conditions, not the model.
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.
Intelligent document processing extracts and validates data from invoices, forms, contracts and scanned records. Extraction without validation produces data that looks precise and cannot be trusted.
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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