AI that delivers business value
Helping companies deliver strategic gains and operational efficiencies with their AI and machine learning initiatives
Support for every stage
AI maturity happens in stages. We'll help you navigate them.
We will help your team build a long-term development plan so that no matter what stage of AI and machine learning maturity your organization is, you can proceed methodically forward, growing your team, developing your culture, improving your process, and strengthening your systems.
Foundation Stage
You are solving a few use cases, while building team, systems, and processes. If you get some wins here, you'll be able to bring this approach to more areas of the business. This stage is all about building a foundation for future growth.
Growth Stage
Your team has a system for generating models but it's painful, and pretty manual and not that trackable, auditable, or reproducible. Work is often duplicated, and production speed is erratic. But you're producing models.
Scale Stage
You regularly build new products and services with AI/ML at the core. You have some automation. But there may be gaps and you're hampered by not being able to scale up fast enough or create enough new products in parallel.
AI-Driven stage
AI has infused every aspect of your enterprise, in all functions and areas. You have end-to-end automation of the entire process. You lead your industry by having AI augment your people in every function, every unit, and every offering to your customers.
What stage are you in?
We can help assess your stage and work with you to come up with a tailored plan to get you safely to the next stage.
People are the heart and soul of AI
AI is a Team Sport
We'll help you design and structure your team for success. We have machine learning engineers, business analysts, AI architects, and project managers who can help you accomplish your projects faster.
Fairness and accountability need to be built in
We believe that fair, responsible, ethical, inclusive AI is the only kind worth building. We'll work with your team to build this into the very foundations of your culture, processes, and systems.
Let's talk about people
Do you need to scale your team? Contact us and let's talk about how we can accelerate your projects and initiatives.
Great AI Requires Great Process
Let's improve your Model Development Lifecycle
The time for ad-hoc model creation processes is over. You can not build trusted AI and machine learning systems if you do not have a well-defined and rigorous process to define and scope the problem, collect and prepare the data, develop and train the models, get those models into production and them monitor them to ensure they are still doing their jobs correctly. Let's work together to continuously improve your model development process.
Data Collection and Preparation
We will help you build a culture and a discipline around good data preparation operations. Big data is good, but good big data is better.
Model Development and Training
We will help your team build a complete process for developing, tuning, experimenting with, and selecting models.
Model Deployment and Operations
We will help your team realize that getting to production means you're "halfway there" and now those models need to be monitored and operated until they are retrained or decommissioned.
Security from Top to Bottom
AI and machine learning comes along with new security threat vectors. Our team will help you secure your systems from new and emerging AI-ML threats.
NOTE: You may have heard the term "MLOps". While there are many definitions of the term, we consider it to be the feedback loop between Model Development and Model Deployment. We will help your team become experts at this newly emerging discipline.
Let's talk about process
Having a complete end-to-end Model Development Lifecycle is critical to long-term success. Anybody can build a few one-time models. But for repeatable, auditable, scaleable AI, you need a well designed end-to-end Model Development Lifecycle. Contact us and let's work together on improving your production processes so that you can stop hand-crafting models and start producing them on a high-quality production line.
Great Platforms Enable Great Teamwork
Platforms are the future of AI and ML
DIY machine learning is fine for the lab but not suitable for production AI at scale. By some estimates, it can cost you millions of dollars to build and millions of dollars per year to maintain your own DIY system that has no data or model lineage, can not be audited, and does not output explainable or reproducible results. In other words, it lacks governance. No governance means more risk.
By using industry-leading platforms, your team can be up and running immediately so you can focus all of your team's time on identifying, clarifying, and working to solve problems that will push your mission forward. Not only that, they come with key elements such as fairness and bias tools, reporting, logging, and data and model lineage that are important to regulatory agencies.
We work with three of the leading platforms in the market and we will help you evaluate, select, implement, and get operational on the platform that serves your organization best.
Value delivered by Dataiku to customers:
Enabled 7x faster production of models for a financial services company.
Enabled 5x more efficient model production for an insurer.
Helped an internal marketing team deliver customer segmentation recommendations 4x faster .
Reduced deployment time 96% (from 3 days to 3 hours) for a builder while also reducing customer churn 60%.
Boosted marketing effectiveness 2.5x.
Dataiku is recognized as a market leader by Gartner, Forester, OMDIA, and IDC.
Value and ROI examples from AWS:
Cut model training time from 3 days to 10 hours for a railway data science team.
Reduced mortgage closing meetings from 1h to 15 min with 75% fewer errors.
Reduced training time from months to days and training costs by 75% for a fintech startup.
Detect fraud for 100M+ customers.
Helped a fintech get credit results returned in 20 seconds vs. 3-5 minutes from the prior platform.
Amazon Web Services is recognized as a Leader in Gartner's Magic Quadrant for Cloud AI Services
According to Forrester Consulting, customers using DataRobot can realize $4M in value and get an ROI of 514% with payback in less than 3 months. (See the study)
Some specific customer examples in the study included:
Reduced model production time by 90%.
Reduced overstaffing by 60%.
Decreased fraud costs 55%.
Reduced ML model production time by 90%.
DataRobot is recognized as a Visionary in the 2021 Gartner Magic Quadrant for Data Science and Machine Learning Platforms.
Need help selecting a platform?
We can help you assess your needs so that you can find the right platform to build your business on.
Our goal is to make your team self-reliant
AI is not something you want to outsource forever
AI needs to be a fundamental organizational and technical capability of your firm. We'll work with you to build up your people, process, and technologies so that you can go dominate your industry. Here are our services to help your team get up to speed.
AI Strategy & Planning
Workshops
Use Case Identification
Audits & Assessments
AI program development
Team development
Project Definition
Refining business problems
Scoping projects
Defining pilots and MVPs
Managing and refining process
Platform
Current architecture audit
Platform evaluation
Platform recommendations
Platform stand-up
Platform training
Infrastructure
Cloud Audit
Hybrid Cloud AI planning
Hybrid Cloud for AI managed services
Security
Data Preparation
Data Audit
Data Acquisition
Data Enhancement
Data Transformation
Data Triage
Modeling
AutoML training
Model development
Model training
Distributed computing
Model scoring
Deployment and Operations
Deployment
Performance monitoring
Accuracy monitoring
Cost monitoring
Governance
Fairness
Bias-detection and mitigation
Explainability
Reporting
Let's chat
Click the button below and let's have a conversation about your business goals and objectives.