
Before you automate: what has to be in order in your data
Why solid data foundations decide whether automation works
Hi. We're Kirana Labs, a software development and AI firm with a nearshore delivery center in Monterrey, Mexico. As a strategy and execution partner, we plan the next version of your business with you, build it with our own team, and stay accountable for the numbers until they hold. Strategy, execution, and AI where it moves the result, for companies in the US and Latin America.
Trusted by founders and operators in the US and Mexico
What we do
For founders and new ventures. From first version through validation, consolidation, and scale, with product leadership inside your team.
For established companies. We find the bottleneck, tie the plan to your P&L, and own a 3:1 return.
For any company that wants AI to work on real business data. We make your data available, unified, and safe for agents to read and act on.
For US product companies. Senior teams in your time zone, accountable for time to market and roadmap milestones.
Every project starts with a number and ends with a report against it.
We write down today's number, from your own data.
Owners, dates, and the number each initiative is meant to move.
Our team does the work across people, processes, systems, and agents.
We report against the baseline on a fixed schedule until the result holds.
Fixed price where the scope allows it. Milestone-based where it doesn't.
Three engagements, in the same format we use for all of them.

Quality-control data on automotive production lines lived on paper and in spreadsheets. We built the mobile capture and KPI layer the line now runs on.

A growing franchise network with CRM, service, and inventory in separate systems. We built the operating platform they use to add franchises.

A GovCon intelligence firm migrating off a CMS onto a custom platform. Our embedded team took ownership of delivery.
Our reach
The industries change. The way we work does not: a baseline, a plan, and a result we report against.
We build with
Direct partnerships with the model and platform providers we build on. Model-agnostic by design.
What we've learned about data, operations, and shipping software, written for operators.

Why solid data foundations decide whether automation works

The primary difference between AI agents and traditional automation (often referred to as Robotic Process Automation or RPA) lies in their underlying logic and capacity for independent decision-making. While traditional automation is deterministic, following rigid, pre-defined rules, AI agents are probabilistic, using reasoning and adaptation to achieve complex goals.

From ambitious startups to established enterprises, the journey of bringing a software product to life is filled with both challenges and triumphs.

In the software world, each project has its own complexities, and choosing the right technological stack for your core software is always important.
Tell us the number you want to move: a launch date, a cost, a cycle time, a cash position. We'll come back with a baseline, a plan, and what we'd be accountable for.