{AI Case studies}
Our Experience in AI & Innovation
Our past successes and diverse expertise drive the innovative AI solutions we deliver today.
How the Elementera team built a tailored AI roadmap for an ad platform, pairing quick prompt engineering wins with long-term use of its historical data.
Meet AdCraft, an SEM simulation platform built with Monte Carlo and agent-based modeling so marketers can test bids and budgets in a risk-free setting.
Research co-authored by Elementera’s Soroush Mehri (EACL 2021) uses hard-to-learn examples to make language models rely less on shortcuts.
A deep reinforcement learning algorithm using policy gradients and variance reduction to help autonomous robots learn and decide in sparse reward settings.
How a legacy Rails store navigation system was migrated to a modular React and GraphQL architecture for faster performance and easier maintenance.
SampleRNN, first-authored by Elementera co-founder Soroush Mehri at ICLR 2017, generates raw audio one sample at a time for music, speech and sound.
An AI system using deep learning and NLP to turn unstructured social media data into trend forecasts that help brands fine-tune marketing in real time.
Conditionally shifted neurons, co-authored by Elementera’s Soroush Mehri at ICML 2018, let AI models adapt to new tasks on the fly from a few examples.
How Char2Wav, co-authored by Elementera’s Soroush Mehri, turns written text straight into speech audio with one neural model trained end to end.
How the team delivered a subscription management app that helps e-commerce merchants streamline recurring sales and keep their customers coming back.
How the Elementera team designed and tested a disaster recovery strategy for a SaaS product, with failover, backups and replication to minimize downtime.
A hierarchical API locking mechanism for a SaaS platform that protects data integrity, cascades locks to dependent resources and logs every lock action.
A NeurIPS 2021 benchmark co-authored by Elementera's Soroush Mehri compares bias mitigation methods for deep learning on shared data and metrics.
Building a fine-grained role-based access control system that gives a SaaS platform secure, scalable permissions across organizations and projects.
A product lifecycle system that lets e-commerce merchants move products cleanly between active, archived and draft states across their sales channels.
How a secure, scalable webhook system brought real-time notifications for identity and secret changes to a SaaS platform and its external integrations.
Native storefront APIs that bring upsell features like pre-orders and subscriptions straight into cart and checkout to help merchants grow order value.
To unlock AI on confidential data, the team combined differential privacy and homomorphic encryption to train reinforcement learning policies securely.
Successor Feature Sets, co-authored by Elementera’s Soroush Mehri (AAAI 2021), helps reinforcement learning agents adapt to new goals and rewards.
A visual drag-and-drop workflow builder and dynamic rule engine created to help construction organizations automate processes and enforce business rules.
How a centralized credit card and wallet management system was built to give a large e-commerce platform scalable, secure payments for millions of buyers.
How imitation and reinforcement learning were used to predict player inputs frame by frame, tackling latency for smoother, faster multiplayer gameplay.
Predictive battery health analytics for a postal and courier fleet’s mobile devices, built to replace blanket yearly battery swaps with targeted care.
An accessible React tree component with deferred rendering and drag-and-drop, built to let merchants navigate hierarchical data with over 10,000 nodes.
How the team added multi-factor authentication with Duo, PingID and Okta integrations to strengthen platform security and meet enterprise requirements.
A custom project management information system that centralizes planning, resources and reporting for construction teams working across many sites.
Combining deep learning forecasts with a deep reinforcement learning agent, this marketing engine optimizes ad bids and budgets in real time.
A personalized program search built with SageMaker, PyTorch and OpenSearch that ranks educational programs by each student’s likely admission success.
An ML-driven semantic search system that helps employees find information in large document repositories by understanding meaning, not just keywords.
How a conditional Wasserstein GAN learned from historical campaign data to generate ad configurations that lift performance and cut manual effort.
