Templefield Technologies
Selected work

Delivered systems, measurable outcomes

Production-grade systems and applied AI engagements evaluated against defined business outcomes — from real-time claim scoring and NLP-driven investment signals to petabyte-scale record linkage.

11
Reference projects
5
Industries served
3
Clients with repeat engagements
5+ years
Documented delivery track record
01 · Finance

AI-based investment signal development and TradingAgent workflow orchestration

Ampega Asset Management GmbH

Pending — engagement in progress

A production-grade investment signal and multi-agent TradingAgent workflow are being developed for integration into the client’s existing investment process in Bloomberg BQuant.

Bloomberg BQuant EnterpriseLLMsPython
02 · Finance

Snowflake data platform for credit analysis and portfolio management

Ampega Asset Management GmbH

Pending — engagement in progress

A test-covered Snowflake and dbt foundation consolidates security issuers, identifiers, analysts, coverage and securities into a governed, fully historized source of truth for credit analysis and future ML use cases.

SnowflakedbtDagster
03 · Healthcare

ML-driven approval prediction for dental prosthesis claims

AOK Systems GmbH

16%Average decision time reduction

A real-time Kubernetes ML platform delivered to multiple AOK health insurers automates straightforward approvals and flags complex cases for human review, with data protection and regulatory compliance embedded by design.

KubernetesMLflowFastAPI
04 · Finance

NLP-enhanced stock performance forecasting

Ampega Asset Management GmbH

20%Annualized return

Analysis of over 90,000 earnings-call transcripts generated communication-derived features that, combined with financial fundamentals, produced a differentiated, data-driven trading strategy.

Bloomberg BQuant EnterpriseApache SparkTransformers
05 · Healthcare

AI-driven hospital invoice verification

AOK Systems GmbH

16%Cost reduction per invoice

A scalable, microservices-based AI system improved invoice-verification accuracy and efficiency while guiding manual processing and reducing the cost per invoice.

PyTorchFastAPIKubernetes
06 · Healthcare

Machine learning-driven customer segmentation

Unilabs AB

11% / 14%Conversion / upselling increase

Actionable customer segmentation clarified market potential and surfaced profitable expansion opportunities, supported by a data-governance framework for targeted marketing and sustained growth.

XGBoostSQLMicrosoft Azure Data Lake
07 · Publishing

GenAI for text summarization in German

Confidential Client

31%More articles processed without additional headcount

An economical, automated summarization platform met the client’s editorial quality benchmarks, reduced costs and enabled staff to focus on higher-value editorial work.

Llama-3Hugging FacePEFT / LoRA
08 · Public Administration

Performance optimization of PySpark AI-applications

Stiftung Zentrale Stelle Verpackungsregister

5× / 3×Faster batch processing / lower resource consumption

Runtime and resource optimizations substantially improved the scalability and operational efficiency of the client’s distributed AI applications.

PySparkScalaMLflow
09 · Public Administration

Deployment of PySpark AI-applications

Stiftung Zentrale Stelle Verpackungsregister

Production deployment

Locally developed PySpark AI applications were deployed to a production Kubernetes cluster and made accessible to end users with reliable, scalable operation.

KubernetesArgoCDApache Airflow
10 · Public Administration

End-to-end record linkage pipeline

Stiftung Zentrale Stelle Verpackungsregister

12%Fraud detection increase

A distributed XGBoost-on-Spark system linked internal records with heterogeneous external sources at petabyte scale, streamlining manual review for the prosecution of fraudulent entities.

PySparkXGBoostKubernetes
11 · Telecommunications

Customer churn prediction

Confidential Client

7%Churn-rate reduction

Automated identification of at-risk customers powered targeted campaigns that reduced churn and helped the client protect and expand its market share.

XGBoostMLflowKubernetes
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