KIIRO LIMITED • AI & Software

We design and build AI-native products that move markets.

Product strategy, machine-learning driven engineering, and beautiful UX — united into pragmatic roadmaps and shipped with relentless quality.

How we partner

Three disciplined phases to move from strategy to production-grade AI.

01

Discovery & Strategy

We identify real user problems, measure opportunity, and define a product roadmap prioritizing impact.

02

ML-First Engineering

Production-ready models, robust data pipelines, and clean APIs — built with observability and compliance in mind.

03

Continuous Delivery

Deploy, monitor, and iterate. We ship measurable value and embed product-thinking into engineering practices.

What we do

Services crafted for teams building high-leverage AI products.

Custom ML Models

Tailored models trained for your data and production constraints.

Product Design

UX systems that foreground explainability and adoption.

Platform Engineering

Reliable infra, observability, and security for AI at scale.

Data Strategy

Data governance and pipelines tuned for model performance.

MLOps

CI/CD for models, reproducibility and lifecycle automation.

Integration & API

Secure APIs and product integrations for rapid adoption.

Let’s talk about your product

Fill out the form and we’ll reply within 48 hours to schedule a discovery call.

Tell us about your goals, timeline, and any constraints.
We keep data confidential.

What to expect

After you submit, we review your message and prepare a short intake. During the discovery call we'll align on outcomes, metrics, and a proposal.

  • Outcome-focused scope and pricing
  • Security and IP protections
  • Clear success metrics and milestones

Ready to move from prototype to production?

We help teams ship faster with production-first ML practices.
Contact our team

Trusted partnerships

What product teams say after shipping with us.

Maya R.
Head of Product

KIIRO scaled our recommendation engine into production with measurable uplift in engagement. The team shipped with clear priorities and excellent code quality.

Liam H.
CTO

They brought rigor to ML lifecycle and made our deploys reliable. Observability and tests were excellent.

Sofia K.
Product Lead

Strategic and pragmatic — they focused on measurable outcomes and shipped fast iterations that users loved.

Frequently asked

Short answers to common questions about engagement and delivery.

How long does a typical engagement take?
Typical discovery and initial delivery ranges from 6–16 weeks depending on scope. We prioritize incremental value delivery.
Do you work with existing teams?
Yes — we integrate closely with product and engineering teams to transfer knowledge and improve processes.
How do you handle data privacy?
We establish clear data contracts, minimal retention by default, and sign NDAs. Security is embedded in our pipelines.