Teams shipping their first AI feature
From idea to deployment with the guardrails to keep it honest in production.
Expertise
AI & Machine Learning
Production ready ML systems, generative AI assistants, and data driven automations.
- Senior engineers from kickoff to ops
- Production tested patterns
- Long term support included
- Capabilities LLMs · Vision · Predictive
- Production Monitoring + drift detection
- Stack PyTorch · LangChain · SageMaker
- Engagement PoC to production rollout
Overview
What we do, in plain English.
AI delivers value when it is shipped, monitored and maintained not when it stops at a notebook. We build models, integrations and operational pipelines that move real metrics in your business, with the guardrails to keep them honest.
Quick wins we deliver
- LLM integrations
- Computer vision
- Predictive analytics
- MLOps pipelines
Who it's for
The teams we partner with on ai & machine learning.
If any of these sound like you, the conversation starts well.
Companies with data, not models
Turn historical data into forecasting, scoring or recommendation models customers feel.
Operators automating with generative AI
Custom copilots, retrieval augmented chat and agentic workflows that actually work.
Capabilities
Where we add the most value.
A focused set of capabilities, each one battle tested in production.
Generative AI & LLM apps
Custom copilots, retrieval augmented chat and agentic workflows on top of Claude, GPT and open source models.
Computer vision
Object detection, OCR and quality control models for retail, manufacturing and security use cases.
Predictive analytics
Forecasting, churn, fraud and recommendation models built on your historical data.
MLOps & deployment
Reproducible training, model registries, drift monitoring and safe rollouts.
AI strategy & enablement
Use case discovery, ROI modelling, data readiness audits and team upskilling.
Why teams choose NerdHerd
What you get with us that you don't get elsewhere.
Models that ship, not notebooks
Production deployment, monitoring and drift detection are part of every engagement.
Honest evaluations
We measure what matters and refuse to call a demo a feature.
Senior ML engineers, not juniors
The same team scopes, builds and operates what they ship.
How we work
A clear path from idea to production.
Four phases, no surprises, designed so you can see progress every step of the way.
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01
Identify a use case with a clear, measurable outcome
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02
Validate feasibility with a focused proof of concept
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03
Productionize with monitoring, evaluations and human in the loop
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04
Iterate based on real world feedback
Deliverables
What you receive at the end.
A short, honest list of the artefacts a typical engagement leaves behind.
- Trained models with evaluation reports
- Production deployment pipeline
- Monitoring, drift detection and alerting
- Documentation for in house handover
Related expertise
Other disciplines that pair well.
Cloud Solutions
Architect, migrate and operate workloads on AWS, Azure and GCP with confidence.
Learn moreDevOps Services
Automated CI/CD, infrastructure as code and observability that ship faster, safer.
Learn moreData Science
Turn raw data into a strategic asset with modern warehouses, pipelines and dashboards.
Learn moreReady to talk ai & machine learning?
Pick the path that fits, a tailored assessment, a written brief, or a no commitment chat with a senior engineer.