Artificial Intelligence · Build
We build generative AI into defined workflows — drafting, summarising, extracting, assisting — rather than deploying an open-ended tool and hoping it is used well. Output is grounded in your own approved content so answers can be traced to a source, and a person stays in the loop wherever the consequences warrant it. We treat prompt injection and data leakage as first-class risks, not afterthoughts, because generative systems read content they do not control. Cost and latency are modelled per transaction so the economics are known before volume scales, not discovered afterwards.
In short
Generative AI solutions apply text, image and code generation to specific business tasks, with grounding, review and cost control built in. The discipline is in choosing tasks where the output can be checked and the cost of an error is understood.
Start a conversationWhat we do
We pick tasks where the generated output is checkable and the cost of an error is understood before anything is built. Scoping tightly is what separates a useful assistant from a demo that impresses and then disappoints. The boundary of what the system will and will not attempt is set deliberately, not left to chance.
We base output on your approved content so that answers can be traced to a source rather than invented. Grounding reduces fabrication and gives reviewers something concrete to check against. Where the model cannot find a basis, it is designed to say so instead of guessing.
We define test sets, quality thresholds, refusal behaviour and the point at which a case escalates to a person. This turns quality from an impression into a measurement that can be tracked across changes. Guardrails cover both what the system should refuse and how it behaves when inputs are adversarial.
We choose a model per task and manage context, caching and volume so unit cost stays predictable as usage grows. Using the largest model everywhere is rarely justified and quietly expensive. The result is an economics model you can plan against rather than a bill that surprises you.
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
Large language model development covers selecting, adapting, hosting and evaluating LLMs for your own tasks and data sensitivity. The right model is the one that meets the task within your privacy and cost limits, which is often not the largest.
Retrieval-augmented generation systems answer questions from your own documents and data, with citations and permission awareness. Most of their accuracy depends on retrieving the right passages, not on the model that writes the answer.
AI agents and automation let software take multi-step actions on your systems, within explicit limits and with an audit trail. The safety of an agent is defined by what it cannot do, not by how capable it is.
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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