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Visionary companies and fast growing startups use GradientJ to scale with software
Business is messy. It's littered with unstructured data from multiple systems tied up in PDFs, unorganized spreadsheets, and even pictures. Growing your business involves sorting through that data to send the right information down to your other downstream processes.
It's not rocket science, but disentangling this data is just complex enough to require a human to review. You can send this overseas, but training people is tough and expensive as you scale. That's why we're teaching software to do it instead.
Process unstructured data in Policy PDFs, Bordereau workbooks, regulatory filings, and other documents to automate submissions, onboarding, and other back office workflows.
Automatically fill out insurance forms and extract billing codes from patient transcripts or streamline patient onboarding from external competitor or legacy systems.
Financial Services
Systematically extract key due diligence items from customer data rooms or distill key unstructured data sources into actionable, structured investment signals.
The status quo
For decades companies have either outsourced manual process overseas through BPO's or have in house-teams running manual processes. While this works, it's not ideal. These teams need to be managed and are hard to scale.
The back office of tomorrow
Advancements in language model technology have unlocked whole new categories of manual processes that can for the first time be automated. These models are capable of handling sophisticated, ambiguous tasks, and once you've trained them once, you can scale them forever
I've seen some promising results using ChatGPT. Can this do anything like that?
Will you be able to help me with my specific task? I didn't see an example of it.
I'm a developer and I want to use this as the foundation of an internal automation we're building.
We're already using a BPO, can we still use this?
I'm a BPO firm, can we use this?
