NaNLABS

NaNLABS is a cloud and data engineering firm based in Argentina that works with startups and growth-stage companies across EV charging, SaaS, cybersecurity, and automotive. The company specializes in building data-native architectures, real-time processing systems, and AI applications for organizations that need to make faster decisions at scale. They work directly with technical teams—often embedded within client organizations—rather than as a traditional vendor.

The firm has delivered measurable outcomes across three core service areas. For cloud data engineering, they've built modern architectures on AWS, Databricks, and Snowflake that have reduced costs (INE saw up to 80% savings during peak usage) and enabled companies to scale analytics without infrastructure headaches. For real-time data processing, they've deployed low-latency systems handling millions of data points per second, particularly for EV charging networks managing 3,000+ stations and IoT-heavy operations. For AI and machine learning, they work on applied models, AI agents for specific tasks (contract intelligence, compliance monitoring), and AI-native development acceleration.

NaNLABS counts several recognizable clients: INE (a global IT training platform), WootCloud (IoT security), Equinix, Delos (insurtech), and a U.S. EV charging network. For WootCloud, they reduced costs by 44% through serverless re-architecture while enabling real-time threat detection. For Equinix, they cut query times by 75% and helped spin an internal tool into a SaaS product. With Privacy Code, they integrated UX design and backend architecture improvements. With IONNA (an EV charging consortium), engineers describe them as "the closest you can have to having an employee working on your team."

Their technical stack centers on AWS (Lambda, Kinesis, Redshift, Glue, Data Pipeline), Databricks, Snowflake, Apache Kafka, and containerized infrastructure. For AI work, they use retrieval-augmented generation (RAG), prompt engineering, and AI agents. They hold AWS Partner Network status and are a Databricks partner. They've earned Clutch 1000 recognition, GoodFirms partnership, and were named a Top AWS Company and Top Staff Augmentation Company.

Services and capabilities

NaNLABS structures its work around three service pillars, though they blend across projects.

Cloud Data Engineering focuses on designing and implementing cloud-native data infrastructures. They handle data optimization (using auto-scaling, Redshift Spectrum, and Databricks clusters to dynamically adjust resources), system integration (consolidating data from APIs, logs, databases, and IoT via automated ETL pipelines), and helping clients choose between data warehouses, data lakes, or data lakehouses. For a cyber risk analytics firm, they built a high-performance Redshift warehouse with automated ETL pipelines and AI-powered insights that sped up risk scoring. For a connected vehicle analytics company, they constructed a Databricks + Redshift lakehouse to support ML model training for predictive maintenance. Infrastructure as Code (IaC) is standard in their deployments.

Real-Time Data Processing targets scenarios where latency matters—EV charger overloads, fraud detection, fleet anomalies. They build event-driven microservices using Kinesis and Kafka to capture high-throughput data with minimal delay. Real-time dashboards and automated triggers enable instant anomaly detection and course correction. For an EV CPO with 3,000+ stations, they achieved 40% less downtime by implementing Amazon Kinesis and Databricks for unified, real-time visibility. For an automotive manufacturer, they built low-latency Kafka pipelines analyzing vehicle telemetry instantly. They emphasize that their systems process "millions of data points per second."

AI & Machine Learning Development spans applied models, task-specific AI agents, and AI-native development. Applied work includes fraud detection, transcription automation, sales automation, and AI-powered knowledge bases. AI agents handle contract intelligence, market intelligence, compliance monitoring, and data reconciliation across systems. For early-stage teams, they offer rapid MVP development in 6 weeks using Cursor and v0, covering code generation, test generation, and documentation automation. They also note that they handle model drift mitigation and fine-tuning for domain-specific accuracy.

Notable work

INE, a global IT training platform serving Fortune 500 companies, faced scaling challenges as their analytics expanded. NaNLABS designed and deployed a scalable analytics ecosystem in 40 days using Infrastructure as Code, achieving up to 80% cost savings during peak usage.

WootCloud, an enterprise IoT cybersecurity company, needed to rebuild its core architecture for real-time data processing at scale. NaNLABS introduced serverless architecture, reduced costs by 44%, eliminated server management overhead, and enabled faster threat detection—transforming the platform into enterprise-ready software.

Equinix worked with NaNLABS (alongside UX studio Secretly Nice) to scale an internal sales tool into a SaaS product. The team deployed hybrid data models and multi-region Kubernetes, cutting query times by 75% and unlocking a new revenue stream.

A U.S. EV charging network backed by leading automakers needed real-time visibility across 30,000+ charging stations. NaNLABS built a cloud-native observability platform ingesting IoT and POS data, automating alerts to prevent disruptions, and creating unified dashboards for key KPIs.

How they work

NaNLABS positions itself as a team extension rather than a vendor. They integrate directly into client teams, approaching projects as if they were their own. The engagement model emphasizes proactive problem-solving—anticipating challenges and providing insights to keep projects on track. They adapt to client pace: from fast-moving startups to complex enterprises. They emphasize clear communication and close collaboration to ensure solutions align with vision and business goals. Specific pricing details are not disclosed on their site, but they indicate flexibility across fixed-price projects, staff augmentation, and ongoing partnerships scaling from Series A through IPO-stage companies.

Team and credentials

NaNLABS does not publicly disclose team size or founder names on their website. They hold AWS Partner Network certification and are an official Databricks partner. They've earned Clutch 1000 recognition as a top 1,000 service provider worldwide, GoodFirms partnership status, and were recognized as a Top AWS Company and Top Staff Augmentation Company. A quote from Greg Svitak, Chief Software Engineer at IONNA, reflects their positioning: "NaNLABS is the closest you can have to having an employee working on your team."