AI, Deployed.
We are your expert partner for deploying Enterprise AI
into production with measurable results.
75% of AI deployments never make it to production.
Despite rapidly advancing capabilities, the majority of CEOs are struggling to adopt AI within their business. A small percentage of companies are successfully deploying AI, and the rest are struggling to keep pace and avoid getting left behind.
Failing to adopt AI does pose an existential threat.
More than 50% of Fortune 500 businesses have been replaced since 2010. Those companies were replaced by ones who used technology to transform how they serve their customers. The rate of technology advancement is now 10X what it was in 2010.
Deployments fail because of integration challenges.
AI systems are designed around data systems and operational processes. Data and operations are what makes your business unique. Successful AI deployments require customization past simply purchasing an off-the-shelf technology. They require an investment in data architecture, business process mapping, and implementation.
We are your partner in integrating AI into your business. We work closely with your team from initial ideation to project delivery. Our approach focuses on mapping use cases and success criteria before progressing to proof-of-concept and ultimately production deployment.
Our Approach
Business Process Mapping
Successful deployments start with a detailed understanding of your existing operational processes. The first step in our engagement is to map and prioritize use cases, while paying close attention to success criteria and metrics that will indicate ROI.
Proof of Concept
We are a full-stack software development agency with experience building frontends, backend systems, data and ML pipelines. We build a proof-of-concept so that we can test results before deploying the solution in your business.
Production Deployment
Once we have established proper governance and guardrails, we help you deploy the solution into a production environment. This includes building evals and analytics so you can monitor and control the system in production.
What works in production?
Production use cases leverage the capabilities of LLMs to process large amounts of text and documents, are high volume, and have a low risk profile.
Insurance
Automate claims, detect fraud, and accelerate underwriting.
These are well-suited for LLMs due to their repetitive, document-heavy nature. Start with the area that aligns with your risk appetite and delivers a fast ROI.
Financial Services
Streamline KYC / KYB, automate risk scoring and compliance.
Given the complexity, it’s smart to begin with a narrow subprocess which requires significant manual effort. There are quite a few of these with low to moderate risk profiles.
Supply Chain
Accelerate procurement, sourcing, and shipment handling.
Integrating legacy data systems is often the first hurdle to overcome. Once data is accessible to the LLMs, high-impact use cases open up quickly.
Retail
Deflect low-risk customer service requests, and process orders at scale.
These are high-volume workflows with repeatable patterns and moderate complexity, which makes them ideal for LLM automation in the low-risk parts of the customer journey.
Examples of our impact
We are a services partner who guides you through scoping, business process mapping, solution design and delivery.
Customer Service Chatbot
Implemented a customer service chatbot for a $100M+ company that deflects 30% of customer inquiries.
The system integrates with CRM, documentation and customer data, providing automated responses while escalating complex issues when necessary.
Insurance Claims Processing
Developed a claims processing system for low risk claims, while maintaining accuracy and compliance standards.
The solution processes documents, extracts key information, and routes claims based on complexity and risk assessment criteria.
KYB Workflow Automation
Implemented KYB workflows for a challenger bank to automate risk review for existing customers, reducing processing time from days to hours for low risk customers.
The system integrates with internal data stores and external sources of information, and escalates all workflows above the desired risk tolerance.
Where do we start?
Our typical engagement model is