AnalystHAUS

Technical clarity for complex enterprise systems

Senior technical consulting for data architecture, integration, migration and performance-critical enterprise applications.

When data structures have grown over years, interfaces span multiple systems and technical decisions affect the entire organisation, AnalystHAUS provides the analytical depth and implementation experience needed to make those systems understandable, reliable and scalable.

Discuss a technical challenge

25+ years of IT project experience · Data architecture · Integration · Migration · SQL and performance

CONSUMERS DATA MODEL INTERFACES SOURCES

Complex systems require more than isolated expertise

Enterprise data rarely lives in one clean platform.

It moves between operational databases, specialist applications, contract systems, APIs, reporting platforms and individually developed interfaces. Changes in one part of the landscape frequently affect several others.

AnalystHAUS supports organisations where technical complexity must be reduced without losing sight of existing systems, business requirements and operational constraints.

Technical consulting

Data architecture

Design and development of robust data structures, data models and information flows across heterogeneous enterprise systems.

  • Conceptual, logical and physical data modelling
  • Analysis of existing database and application landscapes
  • Definition of system boundaries and data ownership
  • Architectural standards and technical documentation
  • Alignment between business requirements and technical implementation

Data integration

Reliable interaction between applications, databases and external services.

  • Interface and API architecture
  • Source-to-target mapping
  • ETL and data-flow analysis
  • Integration of operational and analytical systems
  • Error analysis across distributed processing chains
  • Performance and reliability of data exchange

Data migration

Controlled transition from legacy structures to new systems.

  • Analysis and profiling of source data
  • Mapping, transformation and validation
  • Data quality and reconciliation
  • Migration runs and cutover preparation
  • Post-migration verification and stabilisation
  • Traceable documentation of assumptions and decisions

SQL and data performance

Systematic analysis of performance-critical data processing.

  • T-SQL query and procedure analysis
  • Data-model and indexing assessment
  • Optimisation of complex transformations
  • Identification of bottlenecks in ETL and interface processing
  • Reduction of unnecessary processing and data movement
  • Performance improvements without assuming database operations

Python data platforms and AI integration

Building and operating data platforms in the cloud, including the interfaces that make them usable by AI systems.

  • Python backends and data processing (FastAPI, DuckDB, Parquet)
  • Ingest and transformation pipelines with Apache Airflow
  • Google Cloud operation: Cloud Run, Cloud Storage, IAM, CI/CD
  • LLM integration, tool calling and retrieval-augmented generation
  • MCP servers with authentication, so AI assistants can query your data
  • Cost, latency and quality control for AI components in production

From architecture to working implementation

AnalystHAUS combines architectural thinking with hands-on technical analysis.

The objective is not to produce another abstract target architecture. The objective is to create structures, interfaces and technical decisions that work within the actual enterprise environment.

Understand

Analyse systems, data structures, dependencies, constraints and failure patterns.

Structure

Define clear models, responsibilities, interfaces and architectural decisions.

Implement

Translate the architecture into working data flows, transformations and integration solutions.

Stabilise

Validate results, resolve inconsistencies and ensure that the solution performs reliably under real conditions.

Live reference

TendFeed — built, operated and publicly verifiable

TendFeed (tendfeed.eu) is a European public-procurement intelligence platform built and operated by AnalystHAUS end to end. It is not a case study written after the fact — the system is online and can be inspected.

Data

TED/eForms XML parsed into a corpus of 554,998 contract-award notices (as of 27 July 2026), processed in DuckDB and Parquet.

Pipelines

25 Airflow DAGs for daily ingest, transformation, metrics and monitoring.

Platform

FastAPI on Cloud Run, data in Cloud Storage, separated IAM per service, deployment through Cloud Build.

AI interface

A production MCP server with API-key authentication, publicly listed on glama.ai, plus a product frontend in 24 languages.

Suitable for

  • Enterprise data landscapes spanning several operational systems
  • Integration between CRM, contract, specialist and analytics platforms
  • Legacy modernisation and system migration
  • Inconsistent or insufficiently documented data flows
  • Performance-critical SQL and ETL processing
  • Projects requiring cooperation between data, software and system architects
  • Technical initiatives that need an experienced independent perspective

Senior technical expertise without organisational overhead

AnalystHAUS is led by a senior technical consultant with more than 25 years of project experience in enterprise software, data processing, integration, SQL, reporting and complex system landscapes.

Engagements can range from focused technical analysis to longer-term architectural and implementation support.

  • Direct senior-level collaboration
  • Remote delivery
  • Clear technical documentation
  • Independent assessment
  • Hands-on implementation capability
  • No unnecessary consulting layers

Technical problems become expensive when nobody owns the whole chain

A database issue may originate in an interface.

An incorrect report may originate in a transformation.

A migration defect may originate in an undocumented business rule.

AnalystHAUS analyses the complete path from source system and data model to transformation, interface and consuming application.

The result is not merely a recommendation, but a technically defensible path to a working solution.

Let us discuss the system, not a sales presentation

Describe the landscape, the current technical challenge and the result that must be achieved.