GeniPad is an AI & software consultancy led by a Ph.D. machine-learning researcher. We design, build and run AI systems in production, from document understanding and industrial automation to the web and mobile apps your teams use every day.
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Services GeniPad provides
Services
Four practices, one team. We’ll take you from the first workshop to a system your people rely on every day, and we stick around to keep improving it.
Turn PDFs, scans, contracts, invoices and financial filings into structured, validated data. We read the layout, extract and classify the content, and check facts with LLMs. Every field comes with a confidence score, and anything uncertain goes to a person for review.
Spot problems in sensor data early, plan maintenance before things break, and inspect product quality with computer vision. Runs on the edge or in your plant’s cloud.
AI agents that read, decide and take action across the tools you already use. Built on the Model Context Protocol, with guardrails and a full activity log.
We design and build the products around your AI: internal dashboards, customer portals, mobile apps and APIs. Clean architecture, automated deployments from day one, and the code is yours.
Domain-tuned language models (LoRA, preference optimization, continual learning) that run privately on your own GPUs.
Kubernetes, CI/CD, monitoring, drift detection and rollbacks, so your models stay fast, affordable and accurate long after launch.
Find the highest-ROI automations in your operations, with a clear roadmap, cost model and risk assessment.
How it fits together
Emails, documents, systems of record and sensors flow in. Structured data, alerts, dashboards and actions flow out, and your people stay in the loop wherever you want them.
We parse earnings reports, filings and statements, check every claim against the source documents, and hand your analysts a clean summary with links back to the original pages. Every step is logged, so you can always see how an answer was reached.
Typical outcome
87% → 93%
fact-checking accuracy after domain fine-tuning of an open-weight LLM on financial data.
We learn how your machines and processes normally behave from their own data, then flag anything unusual before it turns into downtime. Computer vision checks output quality at full line speed.
What you get
Real-time
alerts routed to the right operator, with an explanation of what changed and why it matters.
Classify incoming forms, extract every field from scans and handwriting, cross-check against policy data and route only the exceptions to your specialists.
What you get
Exceptions-only
workflows: the routine is automated, your experts spend their time on the cases that need judgment.
Assistants that answer from your own knowledge base. Every answer links to its source, every draft can be reviewed, and nothing is sent to a third party you haven’t approved.
What you get
Cited answers
your team can verify in one click, instead of hours of manual searching.
How we work
Small, measurable steps. You see working software early, and every phase ends with something you can keep.
We map your workflows, data and constraints, then rank automation opportunities by impact and effort.
1–2 weeksA working proof of concept on your real data, benchmarked against an agreed evaluation set.
2–4 weeksProduction engineering: integrations, user interfaces, security, testing and human-in-the-loop review.
4–10 weeksLaunch with monitoring and drift detection, train your team, and keep improving with real feedback.
OngoingResearch-grade, production-proven
GeniPad is founded by Iman Saberi, Ph.D. (Computer Science, University of British Columbia), an applied ML researcher with 7+ years of research and industry experience building foundation models, generative AI systems and large-scale ML infrastructure.
In practice, that means the people working on your project have trained large language models from scratch, put AI agents into production in finance, and published the methods behind them. We bring that same depth to your problem.
Private-cloud and on-premise deployments, least-privilege access, no training on your data without consent.
Evaluation sets, benchmarks, A/B and stress tests before anything reaches production.
Clean code, documentation and hand-over training. No black boxes, no lock-in.
FAQ
Don’t see your question here? Ask us directly. We reply within one business day.
Mostly mid-sized companies and enterprise teams in finance, manufacturing, insurance, legal and the public sector. If your people spend hours reading documents, re-typing data or watching dashboards, we can probably help. We also work with startups that need a senior AI team but aren’t ready to hire one.
Yes, and that’s where most of our projects begin. We start with a short AI Opportunity Assessment. We map your workflows, look at your data, and hand back a ranked list of automations with expected effort, risk and ROI. You keep the roadmap whether or not we build it.
A focused proof of concept on your own data usually takes 2–4 weeks. A production system with integrations, evaluation and monitoring typically takes 6–12 weeks, delivered in small increments you can test along the way.
Absolutely. We regularly deploy open-weight models fine-tuned and quantized to run on your cloud account or on-premise GPUs, so sensitive data never leaves your environment. When a hosted API is the better fit, we will tell you why.
Yes. A model is only useful inside a product people actually use. We design and build the web dashboards, mobile apps, APIs and integrations (ERP, CRM, email, document stores) that put the AI in front of your team.
Before we build anything, we agree with you on how success will be measured: accuracy, hours saved, turnaround time or cost per document. We benchmark before and after, run A/B and load tests, and keep watching the numbers once the system is live.
Start a project
Book a free 30-minute consultation. We’ll look at your process, tell you honestly whether AI is the right tool, and outline what a first version could look like.
