Responsible AI Solutions

With so much chatter around AI these days, it can be difficult for business and technology leaders to cut through the noise and understand how to take the first step toward responsibly leveraging AI in real-world innovation.

Lantern Can Help Light the Way

Here’s why

  • We have years of experience: Unlike most organizations that discovered AI after ChatGPT’s release in late 2022, we have a long history of successfully helping clients deploy AI to optimize their businesses.
  • We use AI to run our own business:  We leverage AI every day for various tasks, from automating coding to rapid prototypes, and even optimizing how we staff projects.
  • We take a human-centered approach: We prioritize a human-centered approach to AI, believing that AI should enhance human capabilities, making individuals more productive and more accurate in everything they do.
  • We have the technical expertise: We have experts in data engineering, app development, UI design, DevOps, and infrastructure architecture – all of which play a role in applying AI to real world solutions.
  • We are a Microsoft Partner: Our close partnership with Microsoft, a global leader in AI, keeps us ahead of the curve so we can help our clients take advantage of the latest industry-leading capabilities as soon as they become generally available.
Real World Examples
Example 1: Improving Employee and Airline Safety 

We helped Unifi, North America’s largest provider of aviation services, reduce risk of accidents or aircraft damage. We built both a predictive and prescriptive AI model. The predictive AI model is trained on hundreds of data points and has learned which patterns in the data (such as elevated overtime, recently hired managers, or inclement weather) have been correlated to past accidents and incidents. The model has shown itself to be 94% accurate in predicting risk 10 days into the future. The prescriptive model takes this one step further by evaluating possible actions which could mitigate this elevated risk and recommending which actions each airport station manager should take prescriptively. Read our full case study for more details.

Example 2: Reducing Tedious Manual Effort in Healthcare Analytics

We helped a healthcare company resolve a time-intensive and extremely manual process involving a team of analysts manually tagging and deduplicating hundreds of thousands of product descriptions as new product descriptions showed up in healthcare purchasing transaction files from partner organizations. We deployed an incredibly accurate AI model using natural language processing technology to automatically match most product descriptions, freeing the analysts up for solving higher value-add problems. As a result, their partner organizations are now able to analyze their healthcare spend data in hours instead of weeks.

Example 3: Identifying Race Cars in Images

We helped a NASCAR race team identify which race car on the team appeared in photos of practice runs so that the technicians could identify problems and correct them before the race. The AI solution used image recognition cognitive services and made the technicians more productive. The team went on to win that year. 

Example 4: Automated Processing of Thousands of Documents Daily 

We enabled a global Consumer Packaged Goods company to drastically reduce the time it took to manually process invoices. We deployed a system trained on hundreds of models to ensure the highest level of accuracy across multiple formats, languages, and geographic locations. Using AI models, our team was able to implement a solution that automatically reads, extracts, processes, loads, and inject invoice data to their SAP system. 


Handled with Care: Our Approach to Data Privacy in the Era of AI

Your data privacy matters to us. Our AI solutions live on the Microsoft platform, so you can rest assured that when you engage with us, your data is handled in line with Microsoft’s data, privacy, and security standards.

This means

  • Your prompts, completions, embeddings, and training data are not available to other customers.
  • Your data is not available to OpenAI.
  • Your data is not used to improve OpenAI models.
  • Your data is not used to improve any Microsoft or third-party products or services.
  • Your data is not used for automatically improving Azure OpenAI models unless explicitly fine-tuned.
  • Your fine-tuned Azure OpenAI models stay within your tenant and under your control.
  • The Azure OpenAI Service is fully controlled by Microsoft and does not interact with services operated by OpenAI.

We Use AI to Run Our Own Business

At Lantern, we practice what we preach. We use AI to enhance our own operations, from automating code-writing to rapidly prototyping solutions and even generating staffing plans for projects.

If you peek into our digital studio operations, you will see

  • Developers using the GitHub Copilot extension for Visual Studio to write test cases for them.
  • BI developers automating the creation of an end-user data dictionary by running a script that asks OpenAI to explain DAX calculations in plain English.
  • Teams leveraging the Azure OpenAI service to rapidly prototype solutions that deliver business value.
  • Staffing coordinators experimenting with GPT-4 using 20+ years’ worth of completed project metadata to create staffing plans, generate document templates, and set future engagements up for success.

Surrounding Expertise

We have a diverse team of experts who can deploy secure solutions in various domains, ensuring success in your AI projects.

  • Advanced Knowledge: Our teams have deep experience in a variety of solution areas, best practices, and emerging technologies both inside and outside of the Microsoft stack.
  • Force Multipliers: Our teams are designed to be force multipliers. Aimed at making everything around us better, strong, and easily scalable.
  • Blended Teams: One of the keys to our success is the ability to empower and enable teams from different backgrounds to achieve a common goal.

As an example, a Fortune 100 Consumer Packaged Goods company had a small data science team with a very labor-intensive process for creating marketing campaigns. They wanted to democratize this solution so that any marketing employee in the company could use their proven process. LANTERN built an intelligent web application with an intuitive UI that allowed any employee to drag and drop household demographics, lifestyle/interests, product propensities and choose their retail stores to target. Behind the scenes, the system queried billions of sales rows, metrics on half a million stores, and demographic info on every US household with response times in under a few seconds. Then it fed these query results to the Python scripts with data science algorithms. We were able to design a secure Azure architecture, automate deployment, and operationalize this proven AI process.

Data is the lifeblood of AI and our data expertise with sizeable datasets was integral to the success of the project.

We Care About Using AI Responsibly

Responsible AI is at the core of our approach. We believe in enhancing human capabilities through AI while ensuring trustworthiness and explainability. We take a human-centered approach, interviewing key stakeholders to gather requirements that align with your expectations of trustworthiness.

  • Foundational Principals: Our team is committed to upholding the Responsible AI standards outlined by Microsoft. These principles include Fairness, Reliability, Safety, Privacy, Inclusiveness, Transparency, and Accountability.
  • Content Moderation: Our systems are designed to classify, identify, monitor, and report any inappropriate content seen by the user or systems.


Lantern can be your guiding light in the era of AI. We have a proven history of delivering successful AI solutions, both for our clients and within our own operations. Partner with us to explore how AI can solve complex challenges in your business and enhance experiences that delighting your customers and drive shared success.

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