Data and Infrastructure Engineering

We build digital solutions for pipelines, warehouses, and databases that support decision-making. From database tuning to constructing pipelines, we create production systems with observability, governance, and cost transparency.

Messy data pipelines and under-optimized databases lead to slow queries and high storage costs. Running an open-source data warehouse with 30TB of data costs nearly $1 million every year. Without a standard framework for your data, decision-making slows down and teams lose trust in the company’s data projects.

GeekyAnts removes these data bottlenecks and storage wastes. We audit your current systems, find the performance blockers, and build a roadmap.

Impact We Make

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400M+ global payments processed annually

The system provides the scalability required to handle millions of transactions while maintaining data integrity and administrative control.

120k+

Active Users in the UK, Canada, Europe, and Australia

400M+

Global Payments Processed Annually

350k+

Downloads Across iOS and Android

3x faster AI feature iteration

The modular backend architecture allowed the team to deploy new AI capabilities and personalized features significantly faster than industry benchmarks.

40%

Reduction in meal decision time

Increase in daily active usage during pilot

Faster iteration on new AI-driven features

$57,000+ Annual Savings

The project achieved a 60% reduction in monthly cloud costs (from $8,100 to $3,300) without any loss in transaction speed or system security.

60%

Reduction in monthly cloud costs

$4800

Saved per month

$57,000+

Annual savings

50% reduction in manual validation cycles

The integration of automated benchmarking frameworks and AI-driven process automation also resulted in 30% faster internal testing workflows.

30%

faster internal testing

50%

reduction in manual validation

Our Core Capabilities

Database Reliability Engineering

We deep-tune PostgreSQL, MariaDB, and Redis to ensure performance and data safety.

Replication Setup
PITR Backup
Query Optimization

Data Pipelines (ETL/ELT)

We build robust pipelines to move, transform, and load data for analytics and machine learning.

CDC
Batch Processing
Stream Processing

Infrastructure as Data

Managing stateful workloads using advanced orchestration patterns.

StatefulSets
Persistent Volumes
Disaster Recovery

Data Engineering Services for Enterprises

PostgreSQL Infrastructure

Advanced tuning and scalable PostgreSQL architecture.

MariaDB Performance

High-availability MariaDB solutions and performance optimization.

Redis Cluster Management

Distributed caching and high-speed data structures

Advantages of Partnering with GeekyAnts

We engineer systems capable of managing Petabyte-scale data without performance degradation

Through the implementation of Materialized Views and specialized engines, we reduce dashboard load times from 30 seconds to under 500ms.

We prioritize Database Reliability Engineering to ensure total data safety.

Backend Engineering Services for Enterprises

Product Backend Studio

We build the "0-to-1" engine for new, high-growth applications.

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Enterprise Backend

We specialize in transforming monolithic legacy systems into modern microservices.

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Cloud & Platform Engineering

We treat infrastructure as code to balance performance with cost.

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Data & Infrastructure Engineering

We build the high-speed pipelines that turn raw data into business intelligence.

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Our Latest Thinking

Insight

Oct 19, 2026

From Kickoff to Delivery: How GeekyAnts Onboards Engineering Teams and Ensures Continuity

This blog explains how GeekyAnts onboards engineering teams through structured ramp-up, knowledge transfer, replacement planning, and continuity practices.

Insight

Oct 19, 2026

Dedicated AI Product Pod vs. In-House Hiring vs. Staff Augmentation: A Cost, Control, and Delivery Risk Comparison

Compare dedicated AI product pods, in-house hiring, and AI staff augmentation across costs, delivery ownership, management effort, and risk to choose the right model for your product roadmap.

Insight

Oct 19, 2026

How GeekyAnts Manages AI Models After Launch to Maintain Security, Control, and Flexibility

AI models don’t stay predictable forever. Discover how GeekyAnts’ documented projects keep model changes in check, catch performance issues, protect sensitive data, and switch providers when requirements change or issues arise.

Insight

Oct 16, 2026

How GeekyAnts Evaluates AI Systems for Production Readiness

This blog explains how GeekyAnts evaluates AI systems for accuracy, security, bias, cost, and performance before production, supported by real project examples.

Insight

Oct 16, 2026

How GeekyAnts Selects AI Tools and Model Providers While Managing Data Security and Client Requirements

Explore the AI tools and model providers used in GeekyAnts’ documented projects, including Claude Code, Gemini, OpenAI, and Ollama. Learn how tool selection, data retention, subprocessors, hosting options, and client requirements shape AI adoption.

Insight

Oct 16, 2026

How GeekyAnts Uses AI in Software Engineering: From Requirements to Release

This blog explains how GeekyAnts uses AI across software development while maintaining human oversight, quality checks, and engineering accountability.

Is your data team fighting high latency instead of shipping insights?

Book a discovery consulting call with our Data Architects today.

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Our Backend Stack

Working with clients across 20+ industries has verified one thing—cookie-cutter approaches do not work when it comes to backend. The backend needs to be tailored for the business and the goal. That is why we do not force one stack on you. We choose the right tool based on performance needs, ecosystem fit, and your team’s expertise.