Generative AI
Custom LLM orchestration and fine-tuning for proprietary enterprise knowledge.
Enterprise AI, built to be trusted
Enterprise AI,
simplified.
We build AI systems that run in production, inside the infrastructure you already own. Most take four to eight weeks from the first call to something your team can actually use.
- deployed in your own infrastructure
- On-prem & clouddeployed in your own infrastructure
- validate ideas, fast
- PoC creationvalidate ideas, fast
- scale what works
- PoC → productionscale what works
Built for regulated, data-intensive industries
- Financial Services
- Healthcare
- Software
- Government
- Manufacturing
- Operations
What we do
Bridge your organization with AI
From a first prototype to a system your compliance team is comfortable signing off on.
Intelligent Chatbots
Agentic workflows that handle complex customer service and internal inquiries.
Workflow Automation
Automation for the repetitive back-office work that quietly eats your team's week.
Predictive Analytics
Models that forecast demand, churn and operational anomalies from your own history.
Computer Vision
Industrial visual inspection and spatial intelligence systems.
MLOps
CI/CD for machine learning, so retraining a model is a routine deploy and not a project.
Our process
How We Work
From the first call to a system running in production, with the price agreed before anyone writes code.
- 01
Discovery Call
A working session. We go through your workflows and whatever state your data is in, then pick out the handful of use cases that are actually worth funding.
A prioritized opportunity map, at no cost.
- 02
Roadmap & Proposal
We turn the strongest opportunity from that session into a written scope with a fixed price attached, so the budget conversation happens before the work does.
A fixed-scope plan with defined ROI and milestones.
- 03
Build & Deploy
We build inside the stack you already run, so nothing gets torn out to make room for us. You see working software every week instead of a status deck.
A production system running inside your infrastructure.
- 04
Govern & Scale
Models drift. We watch accuracy in production, retrain when it slips, and keep the audit trail your compliance team will eventually ask to see.
Ongoing monitoring and support.
Vertical Expertise
Sectors we have shipped into before, where the compliance rules are part of the brief rather than an afterthought.
Financial Services
Healthcare
Software
Government
Manufacturing
Operations
Trust by design
Responsible AI at Our Core.
A model nobody can explain is a model your risk team will eventually switch off. Our Ethos Framework is the checklist every deployment goes through: where the training data came from, who is allowed to touch it, how bias was tested, and what the system is built to refuse.
- Bias Mitigation
- GDPR/HIPAA Compliant
- Model Explainability
- Zero-Trust Data Access
Team
Meet the founders
Three founders, and you work with them directly. There is no account manager in between passing your questions along.
- Co-Founder
Shahram Khalid
AI EngineeringIslamabad, Pakistan
Five years building AI systems that had to survive contact with real users. His work runs from RAG over messy enterprise documents to the Airflow and MLflow plumbing that keeps models retrained, plus the GPU inference infrastructure he built at Norgic.
- LLMs & RAG
- Agentic AI
- Python / FastAPI
- Airflow & Spark
- MLflow & W&B
- Kubernetes & Docker
- Triton & SageMaker
- Co-Founder
Altamash Jawad Chaudhry
Product & DeliveryTallinn, Estonia
Project manager at Ericsson, previously an IT product owner at VARCUS Solutions. He owns the delivery side of an engagement, from the first scoping session through to handover, and does the Lean Six Sigma work for clients whose real problem turns out to be the process rather than the software.
- Product Ownership
- Agile & Scrum
- Lean Six Sigma
- Change Management
- Data Analysis
- Co-Founder
Lishan Fernando
Solutions ArchitectureTallinn, Estonia
Fifteen years of solutions architecture across Europe, the Middle East and Asia. At one company he cut cloud spend by about a quarter while usage was still climbing. At another he built the engineering organization from scratch to twenty people across five countries.
- Solution Architecture
- Azure & DevOps
- SaaS & IoT Scale
- Microservices
- Kubernetes
FAQ
Questions, answered
Quidity is an enterprise AI consultancy based in Tallinn. We build LLM chatbots, retrieval-augmented generation over company documents, and the data pipelines that keep them fed. Everything runs in your own cloud or on-premise environment. We are a consultancy, not a platform vendor, so you own what we build.
Most engagements go from discovery to a working system in production within 4–8 weeks, depending on scope and how ready your data is.
No. Most clients arrive with data spread across systems that were never designed to talk to each other. Building the pipelines and governance underneath the AI is part of the job, not something we expect you to have finished first.
Yes. We deploy into the stack you already run, cloud or on-premise. Your data stays where it is, and the trained models belong to you at the end of the engagement.
We design against GDPR and HIPAA from the first sprint. In practice that covers access control, where data is allowed to live, how bias gets tested, and being able to show why a model produced a particular answer.
We quote a fixed price after the discovery call, once we know what the work actually involves. You approve that number before any build starts, and it only moves if you change the scope.
That is what the discovery call is for. Sometimes the honest answer is that fixing a reporting process will get you further than a model, and we would rather tell you that than sell you a build.
Quidity is based in Tallinn, Estonia and works with clients worldwide, remotely or on-site. It was founded by Shahram Khalid (AI engineering), Altamash Jawad Chaudhry (product and delivery), and Lishan Fernando (solutions architecture).
Ready to put AI to work?
Book a free 30-minute call. You will leave with a written list of where AI is worth your money, and where it isn't.
Schedule your discovery call