Data · Consulting · Engineering · AI · Software

Engineer Your Data.
Accelerate Your Business.

We help companies harness the power of Elastic Stack, Generative AI, and intelligent automation to transform raw data into operational advantage.

Technologies we partner with

What We Do

End-to-End Data & AI Solutions

From observability to AI integration, we cover the full spectrum of modern data operations.

Elastic Stack & Observability

ELK stack deployment, log analytics, APM, SIEM, and real-time monitoring dashboards for complete system visibility.

LLM Integration & Strategy

Custom LLM deployment, A2A architectures, RAG pipelines, context engineering, and model evaluation for your use cases.

Generative AI Solutions

AI-powered content generation, intelligent document processing, AI agents, chatbots, and copilots.

Business Applications & Microservices

Enterprise apps, microservices, event-driven and distributed architecture, full-stack systems end to end.

Business Process Automation

Workflow automation, ETL pipelines, system integration, CI/CD, and infrastructure as code.

Data Consulting & Architecture

Data strategy, architecture design, migration planning, compliance audits, and team enablement.

How We Work

From Discovery to Delivery

A proven process that minimizes risk and maximizes value at every stage.

01

Discover

Free

We audit your current stack, identify gaps, and map out opportunities. You get a clear picture of where you stand and where to go.

02

Architect

Week 1

We design the solution, define the roadmap, and align on timelines and costs. No surprises, full transparency.

03

Build

Weeks 2-6

Agile implementation with iterative delivery. You see progress every week and can steer the direction as we go.

04

Optimize

Ongoing

We monitor, measure, and continuously improve. Your systems evolve as your business grows.

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Technologies

Our Technology Stack

We work with the best tools in the industry to deliver robust, scalable solutions.

Search & Analytics

ElasticsearchLogstashKibanaBeatsGrafanaPrometheus

AI & Machine Learning

OpenAILangChainHugging Face

Platforms & Infrastructure

KubernetesOpenShiftDockerTerraformAWSGCPLinuxNginxHAProxy

DevOps & CI/CD

GitHub ActionsArgoCDAnsibleJenkinsGitLab CIHelm

Data & Streaming

PostgreSQLOracleRedisApache KafkaAirflow

Development

JavaSpring BootTypeScriptPythonRustReactNext.jsNode.js

Testimonials

What Our Clients Say

datasops built us a complete training and gym management system that replaced five different tools we were juggling. My trainers save hours every week and clients love the app.

Marcin

Gym Owner

We needed a system that could handle the chaos of water damage restoration — site photos, moisture readings, technical reports, insurance docs, all in one place. datasops built us a custom CRM that ties it all together. Now every job is documented from first call to final sign-off.

Grzegorz

Owner, Structural Drying Company

The automation workflows datasops built saved us 200+ hours per month. Best technology investment we’ve made this year.

Piotr

Director of Operations

Who We Are

Meet the Founders

Three engineers who believe great technology consulting starts with deep technical expertise and honest advice.

MR

Mateusz Rybak

Co-Founder

Specializes in software development and distributed systems. Turns complex requirements into production-ready systems.

PS

Patryk Sikora

Co-Founder

Expert in Elastic Stack, infrastructure, and AI integration. Builds data platforms and observability solutions at enterprise scale.

AS

Arkadiusz Sieczak

Co-Founder

DevOps Engineer turning complex infrastructure into automated, reliable systems — from bare metal to GKE. Passionate about open-source, with a research background in blockchain and cybersecurity.

From the blog

Latest insights

Deep-dives on data engineering, observability, and AI in production.

DagsterApache AirflowData Engineering

Dagster vs Airflow — Choosing the Right Data Orchestrator for Modern Data Stacks

A comprehensive comparison of Dagster and Apache Airflow for data orchestration: Dagster's Software-Defined Assets model vs Airflow's task-centric DAG approach, asset lineage and freshness policies for data-aware scheduling, Ops and ConfigurableResources vs Operators and Connections, IO Managers for storage-agnostic asset materialisation, partition-based incremental processing with DailyPartitionsDefinition and MultiPartitionsDefinition, Dagster's built-in unit testing via materialize() and build_asset_context() vs Airflow dag.test(), the dagster-dbt integration for first-class dbt model lineage across the asset graph, asset checks for post-materialisation data quality validation, Kubernetes deployment with K8sRunLauncher vs KubernetesExecutor Helm chart, Astronomer Astro vs Dagster Cloud hybrid deployment options, and a decision framework covering existing stack investment, partition complexity, testability requirements, and migration cost.

Read more
Apache FlinkStreamingKafka

Apache Flink for Streaming Analytics — Stateful Processing, Windowing, and Exactly-Once Semantics

A practical guide to Apache Flink in production: DataStream API architecture with operators and parallelism model, keyed streams and managed state backends (HashMap vs RocksDB) with ValueState, MapState, and ListState, tumbling and sliding window functions with event-time watermarks and allowedLateness for late data handling, exactly-once semantics with distributed checkpointing (Chandy-Lamport algorithm) and two-phase commit KafkaSink, Flink SQL and Table API for declarative stream-table joins with CREATE TABLE Kafka connector, FlinkKafkaSource with WatermarkStrategy for event-time processing, Flink Kubernetes Operator with FlinkDeployment CRD for production-grade cluster management, backpressure detection and checkpoint monitoring with Flink Web UI and Prometheus metrics, and a decision framework for choosing between Apache Flink, Spark Structured Streaming, and Kafka Streams.

Read more
Platform EngineeringIDPKubernetes

Platform Engineering — Building Internal Developer Platforms That Teams Actually Use

A practical guide to platform engineering in production: the developer tax problem and golden path philosophy, IDP maturity model (wiki through product-grade), Backstage service catalog with catalog-info.yaml component descriptors and Software Templates for self-service scaffolding, self-service Terraform module registry with opinionated modules encoding security and compliance defaults, ArgoCD ApplicationSets with the git generator for pull-request-based deployment self-service, Crossplane Composite Resource Definitions (XRDs) for Kubernetes-native cloud provisioning (RDS, S3, Redis) without exposing raw cloud APIs, DORA metrics instrumentation with GitHub Actions and PagerDuty data for deployment frequency and lead time, and building platform teams as product teams with developer NPS, adoption metrics, internal SLAs, and public roadmaps.

Read more

FAQ

Frequently Asked Questions

Everything you need to know about working with us.

We work across a wide range of industries including finance, healthcare, e-commerce, logistics, and telecommunications. Our solutions are tailored to each client’s specific domain requirements and regulatory environment.

It depends on the scope. A focused observability deployment or automation workflow can be delivered in 4-6 weeks. Larger initiatives like full-scale LLM integration or platform builds typically run 2-4 months. We always start with a discovery phase to align on timelines.

Yes. We offer flexible support and maintenance plans to ensure your systems stay healthy, updated, and optimized. We can also embed with your team on a part-time basis for continuous improvement.

Absolutely. We integrate with your current infrastructure and tools rather than forcing a rip-and-replace. Whether you’re on AWS, GCP, Azure, or on-prem, we adapt our approach to what works best for your environment.

We offer both fixed-price project engagements and time-and-materials contracts depending on the nature of the work. Reach out through our contact form and we’ll provide a tailored estimate within 24 hours.

Security is built into every engagement. We follow industry best practices for data handling, support GDPR and SOC 2 compliance requirements, and can work within your existing security policies and access controls.

Get in Touch

Send us a message

Tell us about your project and we’ll get back to you within 24 hours with actionable next steps.

Prefer e-mail?

hello@datasops.com

We will respond to you within 24 hours.