HOUSTON AWS DATA SCIENCE
Machine learning that runs in production on AWS
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AWS data science consulting in Houston from DESSS covers the full path from business question to working model. Our AWS machine learning consulting in Houston includes data preparation, model development on Amazon SageMaker, deployment, monitoring and the MLOps practices that keep models accurate over time.
Most data science value comes from a few well-chosen problems: forecasting demand, predicting equipment failures, scoring leads, spotting fraud or reading documents. We help you pick the problems where your data can support a reliable model, and where the result will change a decision.
If your data is not ready yet, we start there. Our data warehouse consulting team can build the clean, governed data that good models need.
When to call us
When a pilot model needs to reach production, or when you want to test a use case on your own data.
What you receive
A trained model, a deployment pipeline, monitoring and documentation your team can maintain.
Who it is for
Operations, finance and IT leaders, and data teams who need help with production machine learning.
Where we work
From our Houston headquarters, with an office in Austin, for clients across Texas.
OUR SERVICES
AWS data science consulting in Houston
Our AWS data science services in Houston, TX cover six areas, from choosing the first use case to running models in production.
Use case and data assessment
We rank candidate use cases by value and data readiness, and check that the data in S3, Redshift or your ERP can support them.
Amazon SageMaker consulting
Model development, training and tuning in Amazon SageMaker, using built-in algorithms, AutoML or custom code.
Predictive analytics
Forecasting, classification and anomaly detection models that support planning, maintenance and risk decisions.
ML model deployment on AWS
Real-time endpoints, batch scoring jobs or serverless inference, chosen to fit your traffic and budget.
AWS MLOps consulting
SageMaker Pipelines, Model Registry and Model Monitor so models are retrained, approved and tracked consistently.
Amazon Bedrock generative AI consulting
Assistants, document search and summarization built on foundation models in Amazon Bedrock, grounded in your own data.
COMMON PROJECTS
AWS machine learning consulting in Houston
These are the projects that most often bring Houston teams to us, and how we approach each one.
Amazon SageMaker consulting in Houston
How do you use SageMaker? Our Amazon SageMaker consulting in Houston covers the whole model life cycle: shared Studio environments, managed training, experiment tracking, hosting and monitoring. We set up secure access and cost controls so data scientists can work without waiting on IT.
–SageMaker Studio and domain setup
–Training jobs and hyperparameter tuning
–Experiment and model tracking
–Endpoint and batch hosting
AWS predictive analytics services in Houston
What can we predict? Our AWS predictive analytics services in Houston build models for demand and sales forecasting, customer churn, credit and payment risk, inventory planning and equipment failure. Each model is measured against the method you use today.
–Demand and revenue forecasting
–Churn and propensity scoring
–Risk and anomaly detection
–Results delivered to BI dashboards
AWS MLOps consulting
How do we keep models accurate? Models lose accuracy as data changes. We automate training and evaluation with SageMaker Pipelines, use Model Registry for approvals, and set up Model Monitor alerts for data and prediction drift.
–Automated training pipelines
–Model approval workflow
–Drift and quality monitoring
–CI/CD for models
Amazon Bedrock generative AI consulting
Can we use generative AI safely? Amazon Bedrock gives access to foundation models from several providers through one AWS service. We build retrieval-based assistants with Bedrock Knowledge Bases, add Guardrails for content and data protection, and keep data inside your AWS account.
For a wider AI roadmap, see our AI consulting services.
–Document search and Q and A assistants
–Summarization and extraction
–Guardrails and access controls
–Cost and quality evaluation
AWS data science for oil and gas companies in Houston
How do energy companies use data science on AWS? Houston oil and gas companies use AWS data science for production forecasting, predictive maintenance on pumps and compressors, sensor anomaly detection and reading unstructured field reports. We combine sensor, production and maintenance data in S3 and build models that operations teams can act on.
–Production forecasting
–Equipment failure prediction
–Sensor anomaly detection
–Field report extraction
HOW WE WORK
How an AWS data science project runs
Our AWS data science consulting services follow six steps, with a go or no-go decision before production work begins.
STEP 01
Frame the problem
We agree the decision the model supports, how success is measured and who will use it.
STEP 02
Data review
We profile the data, check quality and history, and fill gaps with pipelines in AWS Glue.
STEP 03
Prototype
Candidate models are built in SageMaker and compared against today's method.
STEP 04
Productionize
The chosen model is packaged, deployed and connected to the systems that use it.
STEP 05
Monitor
Accuracy, drift, latency and cost are tracked with alerts.
STEP 06
Hand over
We document, train your team and stay available for retraining and new use cases.
RELATED SERVICES
Services that support data science on AWS
Good models need good data, solid cloud foundations and reporting people use.
WHY DESSS
Why choose DESSS for AWS data science services in Houston, TX
A model only creates value when it is in production and people use it.
Business problem first
Every project starts with a decision to improve and a way to measure it.
Built for production
Deployment, monitoring and MLOps are part of the plan from the start.
Data and systems experience
We also build data warehouses and integrate ERP and CRM systems, so we can fix data problems at the source.
Local to Houston
Workshops and model reviews can happen in person at your office or ours.
DESSS AWS data science consulting includes use case assessment, data preparation, model development on Amazon SageMaker, predictive analytics, deployment, MLOps and generative AI with Amazon Bedrock.
Amazon SageMaker is the AWS service for building, training, deploying and monitoring machine learning models. It provides managed notebooks, training jobs, hosting and MLOps tools.
SageMaker is for building and running your own machine learning models. Amazon Bedrock gives access to ready-made foundation models for generative AI through an API. Many solutions use both.
It depends on the data and the use case. We aim to reach a go or no-go decision on a prototype early, before committing to production work.
Not always. Many models can start from data in S3 or source systems. If the data is scattered or unreliable, we recommend fixing that first.
Yes. We build forecasting, predictive maintenance and anomaly detection models on AWS for Houston energy companies, using their sensor, production and maintenance data.
HOUSTON AWS DATA SCIENCE
Talk to a Houston AWS data science consultant
Book a short call about AWS data science consulting in Houston. We will discuss your data, your use cases and how to get a first model into production.
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