For Startups
Senior AI and product engineering for startups
From idea to production in weeks, with a nearshore team in your time zone. You talk directly to the engineers building your product.
Book a free discovery callWays to work with us
AI MVP Sprint
One AI feature, live in weeks
A fixed-scope sprint to put one LLM, RAG, or ML feature into production. Written scope and price before we start.
Product MVP
From idea to a product users can try
Web or mobile app plus the backend and cloud setup behind it. Fixed timeline, built to grow after launch.
Dedicated Senior Squad
Senior engineers in your time zone
Nearshore engineers from Brazil who join your team channels and ship with you. Monthly, no long hiring process.
Fractional CTO
Senior technical decisions, part time
Architecture, AI strategy, vendor choices, and code review for founders who do not need a full-time CTO yet. Hourly with a cap.
AI in Production, Not Slideware
Real systems our founder has shipped - with the scale, latency, and timelines that matter.
Conversational AI / Cybersecurity
Cybersecurity ratings platform
12M+
Companies queryable in plain English
6 weeks
Concept to production
AWS K8s
Scalable serving layer
The challenge
A massive security-ratings dataset covering more than 12 million companies was locked behind dashboards and report builders that only technical analysts could use.
What we built
Our founder built an LLM-powered conversational interface that answers natural-language questions over the security-score data, backed by a retrieval layer and served through a fast API. It went from concept to production deployment on AWS Kubernetes in six weeks.
The result
Analysts query complex cyber-risk data conversationally instead of hand-building reports - the same retrieval-augmented pattern we bring to clients in regulated, data-heavy industries.
- LangChain
- HuggingFace
- FastAPI
- AWS
- Kubernetes
Predictive ML / Fintech
Large Latin American credit bureau
1000s
Lenders served
Real-time
Automated credit decisions
Explainable
Auditable model outputs
The challenge
One of Latin America's largest credit bureaus needed credit decisioning that stayed consistent and explainable while scaling across thousands of financial institutions.
What we built
Our founder led the engineering team that built a machine-learning credit engine combining large-scale PySpark feature pipelines with neural-network models that score creditworthiness in production.
The result
Automated, consistent, regulator-ready credit decisions at national scale - the kind of feature engineering and deep learning we apply to turn raw financial data into reliable decisions.
- PySpark
- Neural Networks
- Python
- Big Data
Computer Vision / Public Safety
City-scale public safety network
5min → 30s
Fire-detection latency
100s
City cameras processed live
Real-time
Automated event detection
The challenge
Hundreds of city cameras produced live video that no human team could monitor fast enough to act on incidents in time.
What we built
Our founder designed real-time computer-vision pipelines - automatic license-plate recognition and event detection - that process live video at city scale on OpenCV with TensorFlow and Keras.
The result
Passive camera feeds became an active public-safety system - a near order-of-magnitude latency improvement we reuse anywhere live video must drive instant decisions.
- OpenCV
- TensorFlow
- Keras
- Python
How it works
1
Free discovery call
2
Written scope and fixed price
3
We build and ship to production
Pricing depends on scope. You get concrete numbers after the discovery call, before you commit.
Book a free discovery call
