AI & Machine Learning
Engineering intelligence into every layer of the modern enterprise
Our AI & Machine Learning Center of Excellence brings together senior data scientists, ML engineers, MLOps specialists, and applied research talent to solve the hardest problems in applied intelligence. We design and deliver production-grade AI systems end to end — from problem framing and data strategy through model development, deployment, observability, and continuous improvement. Our practice spans classical machine learning, deep learning, computer vision, natural language processing, recommender systems, and the new wave of generative AI built on large language models. We partner with product companies to embed AI into their core platforms and with service-led enterprises to transform their internal operations with intelligence at scale.
Our 10-year commitment
Over the next decade, every meaningful product and process will be augmented by intelligence. We are investing aggressively in AI/ML talent, IP, and tooling to be the trusted long-term engineering partner for organizations betting their future on AI.
Services we provide
The full breadth of AI & Machine Learning capability we deliver — from strategy and architecture through engineering and operations.
Generative AI & LLM Solutions
RAG systems, fine-tuning of open and closed foundation models, prompt engineering, AI agents, copilots, and domain-specific assistants built on OpenAI, Anthropic, Google, Mistral, and open-source models.
Applied Machine Learning
Classical and deep learning models for forecasting, classification, ranking, anomaly detection, and recommendation — designed for production reliability and measurable business impact.
Computer Vision
Object detection, image segmentation, OCR, video analytics, and visual quality inspection for manufacturing, retail, healthcare, and logistics.
Natural Language Processing
Entity extraction, summarization, semantic search, document intelligence, conversational AI, multilingual NLP, and intelligent document processing pipelines.
MLOps & ML Platform Engineering
Feature stores, model registries, automated training and deployment pipelines, drift monitoring, and end-to-end ML platforms on AWS SageMaker, Azure ML, Vertex AI, Databricks, and Kubeflow.
AI Strategy & Discovery
Use-case identification, ROI modelling, data-readiness assessment, and AI roadmap design for boards, CxOs, and product leadership teams.
Responsible AI & Governance
Bias detection, explainability, model cards, evaluation harnesses, red-teaming for LLM applications, and compliance with emerging AI regulation.
Embedded AI Engineering Teams
Dedicated pods of AI engineers, ML scientists, and platform engineers embedded within client product teams to co-build AI products and ship them to end users.
Clients we have served
Our AI & Machine Learning practice serves both product-led companies building the next generation of software and service-led firms reselling our capability to their end clients.
Client names anonymized to protect engagement confidentiality.
Product Companies
A US-headquartered SaaS unicorn in sales productivity
SaaS / Revenue TechBuilt and shipped the GenAI copilot inside their flagship product, enabling natural-language pipeline analytics and AI-drafted outreach for 100K+ end users.
A global cybersecurity product company (NASDAQ-listed)
Cybersecurity ProductsDesigned the anomaly-detection and behavioural-analytics models powering their SOC platform, processing billions of telemetry events daily.
A leading EU health-tech product firm
Digital HealthDeveloped clinical NLP pipelines and a HIPAA/GDPR-compliant LLM layer integrated into their EHR-adjacent product suite.
A North American fintech scale-up
Fintech / PaymentsEngineered the real-time fraud-scoring and risk models that became the foundation of their flagship anti-fraud product, now resold to other banks.
An APAC mobility platform (publicly listed)
Mobility / MarketplacesBuilt the dispatch optimization, demand-forecasting, and dynamic-pricing engines running across 80M+ monthly trips.
Service Companies & SIs
A top-5 global IT services firm
IT ServicesLong-running partnership delivering AI/ML engineering capacity into their banking and insurance practice — staffing 40+ engagements across 3 geographies.
A Big-4 consulting major (US practice)
Management ConsultingGreenPot acts as the AI implementation arm for several of their Fortune 500 transformation programs in retail, supply chain, and healthcare payers.
A specialist data & analytics consultancy (UK)
Analytics ConsultingProvide dedicated ML and MLOps pods that ship under their brand into European banking and pharma clients.
A US system integrator serving the public sector
Public Sector ITGenAI and document-intelligence specialists embedded into their federal and state-level modernization programs.
A global Salesforce + Data SI partner
CRM / Data ServicesJoint delivery of predictive-CRM, AI-augmented Service Cloud, and Einstein extension work for shared enterprise clients.
Engineers embedded inside your product team
A significant share of our AI/ML work is delivered through engineers that are outsourced to our clients — embedded inside their squads, reporting into their product and engineering leadership, and shipping code directly into their production systems. For product companies this means we co-build their flagship AI features. For service-led companies and SIs, our engineers ship under our partners' brand to their end clients. We obsess about retention, continuity, and engineering quality — the engineers you start with are the engineers who stay.
A NYSE-listed SaaS product company
Dedicated AI pod embedded in their R&D org, co-owning the roadmap for two AI features that now drive a material portion of platform revenue.
A global IT services major
AI/ML capacity center delivering into their banking, insurance, and retail practices — engineers ship under their client-facing brand.
A US digital-health scale-up
Embedded clinical-NLP and LLM engineering team owning the GenAI surface of their EHR-adjacent product.
A European Big-4 consulting firm
On-demand AI/ML pods that flex up and down across their Fortune 500 transformation programs in Europe.
Selected Case Studies
Anonymized engagement stories. The full library lives in our case studies hub.
GenAI copilot inside a Fortune 500 sales platform
Problem
A SaaS leader needed to ship a GenAI copilot inside their flagship product within two quarters — but lacked the in-house LLM, RAG, and evaluation expertise.
Approach
We embedded a 10-engineer pod alongside their product team, built the RAG architecture on top of their data warehouse, designed a multi-model routing layer, and stood up an evaluation harness that gated every release.
Outcome
Copilot shipped on schedule and became a headline feature in two consecutive product launches; usage scaled to 100K+ daily active users in the first year.
Impact
Real-time fraud ML platform for a fintech
Problem
A growing fintech was losing material revenue to fraud and could not retrain or deploy its risk models faster than once a quarter.
Approach
Built a streaming feature store on Kafka + Flink, redesigned the model-serving stack on a Kubernetes-native platform, and stood up automated retraining with drift monitoring.
Outcome
Models now retrain weekly and ship to production in under an hour; fraud losses dropped sharply and the platform became a resellable product line for the client.
Impact
Clinical document intelligence for a digital health provider
Problem
Clinical operations teams were drowning in unstructured documents — referrals, lab reports, prior auths — slowing throughput and frustrating clinicians.
Approach
Designed a HIPAA-compliant document-intelligence pipeline combining OCR, fine-tuned domain LLMs, and human-in-the-loop review queues, integrated directly into their workflow product.
Outcome
Document processing throughput tripled, clinician review time per case halved, and the capability became a core differentiator in their next sales cycle.
Impact
Technologies & Tools
The stack our AI & Machine Learning engineers go deep on.
Partner with our AI & Machine Learning CoE
Whether you need a dedicated pod, embedded engineers, or a full program — let's map your goals to our practice.
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