We build AI that actually works.
We reduce costs and boost efficiency by tailoring AI solutions that deliver tangible results for your business.
Building AI since back when it was called machine learning.
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AI projects delivered
1990
Building AI solutions since
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Industries served
Used by the world's leading companies
AgriTech
GovTech
Retail & Logistics
Enterprise Software
Professional Services
Case Studies
Challenge
Traditional herbicide spraying treats entire fields, leading to excessive chemical use, higher costs, and the rise of herbicide-resistant weeds. The challenge was to improve weed detection at the plant level so herbicides could be applied only where needed, while maintaining the speed and accuracy required for real-world farming operations.
Result
Eagerworks collaborated on training the AI models behind See & Spray, using computer vision and machine learning to distinguish crops from weeds in real time and enable highly targeted herbicide application. The system reduced herbicide use by up to 90%, lowering costs and environmental impact while helping combat herbicide resistance and providing farmers with better data for decision-making.
Challenge
KPMG wanted to demonstrate how AI could transform the first point of contact between patients and healthcare systems. The experience needed to simulate a realistic medical triage conversation, understanding a patient's symptoms, history, and medications before determining the appropriate specialist. The main challenge was making the interaction feel natural while processing speech, reasoning, and generating spoken responses in under one second.
Result
The system receives the patient's voice input, understands the conversation, applies medical triage logic, generates a context-aware response, and converts it back into natural-sounding speech for the virtual avatar. Using OpenAI models, ElevenLabs, Python, and AWS, we created a scalable real-time conversational system that delivers a fluid and responsive demonstration of AI-powered healthcare.
Challenge
Target was manually forecasting demand for a large number of toy products using complex Excel-based “ladders.” The process relied on historical sales and vendor targets, but was time-consuming and difficult to scale. Forecasts also had to account for seasonality, holidays, changing consumer trends, and unexpected factors such as viral products or economic shifts.
Result
The AI-powered forecasting platform cut the time for accurate sales forecasts, especially for products with extensive historical data. Users upload their sales targets and calendar events, and an XGBoost-based machine learning model predicts weekly sales for each product across the semester. The system provided more reliable projections, minimized human error, and boosted efficiency in the prediction process.
Challenge
Government teams often rely on previous solicitations when drafting new ones, but finding the right examples becomes extremely difficult across millions of documents. Authorium needed a way to surface the most relevant past solicitations from a database of more than 16 million documents.
Result
Eagerworks built an AI-powered writing assistant that uses embeddings to understand what a user is currently drafting and retrieve semantically similar solicitations from Authorium's document library. This gives users instant access to relevant past examples and helps them write new documents faster using proven content as a reference.
Challenge
Tell a Tale needed to do something deceptively hard: invent a story that children would actually want to listen to, on the spot. The experience had to be safe and age-appropriate, respond to the child's choices, and feel expressive and emotional — all while starting fast enough that the magic wasn't lost waiting for AI to think.
Result
We engineered the entire AI pipeline around real-time storytelling, combining streaming generation, aggressive latency optimizations, safety layers, and expressive voices that bring characters and emotions to life. By generating and narrating the story progressively instead of waiting for everything to finish, we brought the time to first narration down from an expected ~30 seconds to around 3 seconds.
Challenge
Avantel was dealing with a growing number of scam calls across its network. While some suspicious calls could be identified manually, the process didn't scale and many scams went undetected. They needed a way to analyze large volumes of call activity and automatically identify patterns associated with fraudulent behavior.
Result
Eagerworks built a machine learning system that analyzes raw call logs and uses an XGBoost model to identify calls with a high likelihood of being scams. This gives Avantel a scalable way to surface suspicious numbers automatically, so they can block them, investigate recurring patterns, and report fraudulent activity to the authorities.
Challenge
Scouty lets clients upload creative briefs that can span multiple PDF pages and combine both text and images. Understanding those briefs, extracting the real requirements, and matching them against the right locations was being done manually, a process that could take days before the client received a first response.
Result
Eagerworks built an AI agent that extracts what the client is looking for, searches Scouty's listings for the best matches, and automatically prepares a polished shortlist ready to send. By removing most of the manual work from the process, Scouty can now handle far more briefs without scaling the team at the same rate.
Challenge
Audit feedback is highly manual and depends on experienced people reviewing the framework, interpreting the client's evidence, and deciding what is missing or needs improvement. The challenge was not just automating that review, but making sure the AI understood AuditEdge's standards and guidelines, stayed grounded in the evidence provided, and gave practical feedback without inventing requirements or suggesting actions that didn't make sense in context.
Result
Eagerworks built an AI-powered audit assistant that understands the requirements of each framework, reviews the evidence submitted by the client, and generates feedback based on both. The system follows AuditEdge's own standards and review criteria, grounding its recommendations in the available evidence and adding safeguards to reduce incorrect or irrelevant suggestions. This delivers consistent, high-quality feedback while reducing the amount of manual review required.
Challenge
Left Coast Scanning digitizes huge archives for hospitals, schools, and other organizations, but its legacy platform was becoming a bottleneck. They needed to process many different document types, including low-quality scans, and make millions of pages easy to search without sacrificing speed, accuracy, or scalability.
Result
Eagerworks replaced the legacy system with an AI-powered document platform that processes PDFs, scans, and images, extracts and cleans their content, and indexes everything for semantic search. Users can find documents by meaning instead of exact keywords and ask questions directly across the archive, giving Left Coast a modern platform capable of handling millions of documents while unlocking a much better experience for its clients.
Challenge
The Appraisal Lane needed real-time visibility into the US used-car market to improve vehicle appraisals and help dealers make better decisions. That meant continuously collecting data from more than 52,000 dealership websites and tracking over 10 million vehicles every day, while keeping infrastructure costs under control and making billions of historical data points instantly searchable.
Result
Eagerworks built a distributed data acquisition and processing platform that crawls dealership inventories, tracks vehicle movements and pricing, and processes more than 10 million data points per day. On top of that data layer, we added AI to forecast future market trends and vehicle prices. The result is a system that not only shows what is happening in the used-car market today, but also helps dealers anticipate where the market are heading next.
How we work
First we listen.
Then we build.
Every AI project with us follows the same four phases — not because it's a template, but because it's what makes AI actually land in production.
01
Discovery
We meet with you to understand your business: workflows, bottlenecks, team structure, and goals. We also look at your data — what you have, what quality it's in, and whether it's enough to build on.
02
Diagnosis
We identify exactly where AI creates leverage — and where it doesn't. We define the scope, set measurable success criteria, and agree on a prototype before committing to full build.
03
Build
We design and develop the solution tailored to your specific context. We evaluate models, run tests, and actively mitigate risks like hallucinations or data leakage before anything goes live.
04
Measure
We track outcomes and refine until the results are real and repeatable. Monitoring isn't a nice-to-have — it's how we know whether the AI is performing or drifting.
What we do
Four ways we
help your business.
AI Opportunity Assessment
We map your operations and identify the highest-impact areas for AI. You get a clear action plan before any development starts — so you invest where it actually matters.
Workflow Automation
We take the repetitive, rule-based work off your team's plate — classification, routing, data entry — so people focus on the work that needs them.
Custom AI Product Development
From prototype to production: we design, build, and ship AI products tailored to your context, with evaluation and risk mitigation built in.
AI Integration & Advisory
We integrate AI into the systems you already run and advise your team along the way — honestly, including where AI doesn't help.
What AI can do for you
Not sure what's possible?
Here are
some ideas.
Most companies that come to us don't know exactly what they need — they just know there's a better way. These are real use cases we've built or helped define.
Find the right answer, instantly.
Your knowledge is scattered across PDFs, wikis, drives, and inboxes. AI can read all of it and surface the exact answer — with the source attached.
Ask questions in plain language across all your documents.
Retrieve the right clause, policy, or version in seconds.
Summarize long reports into decision-ready briefs.
Keep answers grounded with citations to the source.
The work no one wants to do — automated.
Every team has tasks that are predictable, rule-based, and time-consuming. Not complex enough to require a human, but too important to skip. AI can take these off your team's plate entirely.
Classify and route support tickets by topic.
Automate data entry from scanned documents.
Identify and resolve data issues proactively.
Automate workflows based on email intent and content.
Drafts that write themselves.
Proposals, contracts, and recurring reports follow patterns. AI can generate first drafts from your templates and data — your team only reviews and approves.
Generate contracts and proposals from approved templates.
Turn raw data into recurring reports automatically.
Draft personalized client communications at scale.
Keep tone, format, and clauses consistent across teams.
Eyes that never get tired.
Cameras and image feeds carry signals humans miss or can't review at scale. AI can inspect, count, and flag — continuously.
Detect defects on production lines in real time.
Count and classify objects from drone or field imagery.
Flag safety or compliance issues from camera feeds.
Extract structured data from photos and scans.
A copilot for every team.
Give your people an assistant that knows your processes, your systems, and your data — and answers in seconds instead of meetings.
Onboard new hires with an assistant that knows your playbooks.
Answer policy and process questions instantly.
Draft responses inside the tools your team already uses.
Connect securely to your internal systems and data.
See what's coming before it happens.
Your historical data holds patterns. AI can turn them into forecasts you can plan around — demand, churn, maintenance, and more.
Forecast demand and optimize inventory levels.
Predict churn and act before customers leave.
Anticipate equipment failures with predictive maintenance.
Plan staffing around predicted workload peaks.
Support that scales without headcount.
Most support questions repeat. AI can resolve the routine ones instantly and hand the complex ones to your team with full context.
Resolve common questions instantly, 24/7.
Triage and escalate complex cases with full context.
Suggest answers to agents in real time.
Analyze conversations to find recurring product issues.
The problem
Most AI projects fail. Here's why.
Companies invest in AI tools without knowing which problem they're solving.
Vendors propose technology before understanding the business.
Pilots get built for the wrong process and never scale.
Teams end up with tools they don't use and results they can't measure.
Our Approach
We work
differently.
We start from the business problem, not the technology. Before we write a single line of code, we understand your operations, your team, and where AI genuinely creates leverage.
Business first. Technology second. We'll tell you honestly where AI helps — and where it doesn't.
“Not only are they reliable and talented developers, but they are eager to come to the table as thought partners, sincerely invested in the success of our product. Simply put, we could not have accomplished all that we have without our Eagerworks team members. ”
Jay Nath
Co-CEO City Innovate and ex CIO of San Francisco
“Eagerworks delivered high-quality, personalized work quickly and consistently exceeded our expectations. They adapted to our timelines, brought fresh thinking, and showed a strong understanding of today's hardware and software landscape. ”
Jose Rodriguez
Manager at G's Group
Ready to implement AI that actually works?
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