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LARA saves money by greatly reducing the number of billable expert hours per piece of approved content. By eliminating even one review cycle, LARA can save millions when scaled across the enterprise.
Catching errors at time of occurrence makes a huge impact downstream in the MLR process. LARA saves your team time by automating processes that are currently entirely manual. With LARA Review, your team never needs to spend hours proofreading content, looking for a reference page number, or other tedious menial tasks.
Each part of LARA is priced seperately. LARA Research is a fixed monthly fee, LARA Relevance is a fixed monthly fee, and LARA Review is priced based on the volume of content reviewed. All of LARA includes unlimited user accounts and customer support. Lastly, enterprise pricing is available for upwards of 10 brands.
Our illustrative business case (validated by pharmaceutical marketers) shows that when using LARA upfront during content creation (pre-MLR), a US market that produces about 8,000 pieces in one year can save $26 million in external agency costs on rework, save 29,000 internal hours across marketing/operations/RC, and save at least 1 review cycle per asset. The savings increase as volume goes up.
We’ve found a common thread among strategic marketing objectives to be that they all require a higher volume of content. LARA enables this higher volume of content to be produced by freeing up your teams’ time.
LARA Review, our flagship solution, is an integrated set of neural networks that screens promotional materials for common issues that slow down the process of content review. LARA is trained on each brand individually, and learns and grows with your brand over time.
LARA Review Annotate will dynamically correlate claims to references and provide hyperlinks directly to the corresponding lines in the reference file. This information can be exported into a PDF with LARA's annotations as adobe comments.
LARA Research is another functionality of our AI- an auto-generated search engine for claims, safety balance, and references. Simply type a keyword or phrase into the search bar and get immediate results from your library of approved assets.
LARA Relevance is another functionality of our AI- compare your content to customer behavioral data, measure your relevance, see how you stack up to competitors and more.
LARA is intended to be used by anyone upstream of the MLR process: marketers, brand managers, copywriters, or editors. It can also be used by agencies to help streamline content creation. LARA has an intuitive interface that anyone can pick up quickly.
To get the most out of LARA, we recommend using it as far upstream of the ML review as possible, so that by the time the content reaches the desk of review professionals, it is already of high quality and free from common errors.
For LARA Research, simply type a keyword or phrase into the search bar located at the “research tab”. For LARA Review, it’s a simple 3 step process:
- 1) Upload
Log in to LARA in your web browser, attach your files, and click ”upload”. You can leave LARA and take care of other tasks while you wait, LARA will read your content for you and send you an email when complete.
- 2) Review
The custom-built AI will analyze your content line by line, searching for possible compliance issues. LARA will have suggestions for you in moments, covering common errors that slow down the MLR review, across claims, safety information, references, and editorial issues.
- 3) Revise & Repeat
Make changes to your content and re-upload, further refining your piece until it is ready to go. With your content cleaned up before MLR, marketers enjoy drastically accelerated promotional review and increased time to spend on revenue generating activities!
LARA is the cutting-edge product reflecting 6.5 years of research. Our development team includes PhD and Master's level researchers. LARA parses the entirety of a brand’s approved information and draws conclusions regarding what qualifies as a claim, safety, or reference information. LARA’s set of integrated neural networks can parse, analyze, and categorize large amounts of data in a matter of hours, to provide actionable suggestions in minutes for pieces in the pipeline.
After you provide us with approved promotional and reference materials, they are uploaded into LARA and over the course of 6-12 hours, LARA teaches itself the brand and creates a network of claims with correlated safety and reference balance. After learning a brand, LARA is vigorously tested to ensure the highest level of accuracy possible.
LARA can integrate with your DAM to get access to the most current brand data available automatically, without a need for manual updates.
The short answer is years of blood, sweat, and tears spent relentlessly iterating our AI until it met our (admittedly high) standards. We have a talented team with artificial intelligence innovators working on LARA each day to make it smarter, better, and faster.
Currently, LARA supports English pieces; but support for Spanish, French, Portuguese, and Italian is on our near term roadmap.
LARA can review files that are .pdf, .docx, or .pptx files.
LARA is not a claims catalog or a business rules engine, LARA is a sophisticated AI that makes the expert capabilities of a medical, legal, regulatory, and editorial reviewer accessible to anyone, anywhere, anytime. Claims do not have to be manually harvested, updated, or maintained like a catalog does- instead, it can be updated automatically as new pieces are added to your library of approved content. LARA automates the reference tagging process and can draw accurate conclusions from large sets of data.
Getting started with LARA requires almost no lift on your end, all we need are your approved marketing files, references, PI & ISI. We’ll send you an email once your Research workspace is ready in 3 days, and another when your Review is up and running in a few weeks.