How Phospho is re-inventing text analytics from LLM apps

We are in the midst of an LLM era.

And with that has come a surge in LLM integrations (e.g Chat GPT) into most apps today, offering a huge pool of text data from user conversations within them.

This textual data is a goldmine for insights and it’s critically important to get the right data to iterate faster and ultimately take a bigger proportion of the market.

However, most product analytics tools that saw a huge boom over the last decade were not designed for deriving insights from textual data from LLMs.

This is where we, at Phospho, have provided the necessary tools to extract rich insights from your users’ text analytics to iterate effectively and quickly with data driven decisions.

The Explosion of Textual Data in LLM Apps

To provide some perspective, Chat GPT reached 100 million users in just 2 months after its launch. Instagram took 2.5 YEARS.

It’s adoption is understandable and given the practicality of its ability to generate content it has become central to numerous industries:

• Customer service
• Legal and Compliance
• Financial services

The exponential growth of textual data available has created a double edged sword with both challenges and opportunities in managing this data.

Challenges: security and compliance with more personal data at high volume

Opportunities: as mentioned earlier, a rich pool of user insights to action with data driven decisions

The companies that actually leverage this data for streamlined iteration will have a significant competitive edge in the market, but in order to do that we need the right tools…

The Need for Advanced Text Analytics in LLM Apps

Traditional text analytics are insufficient given the rapid evolution of gen AI. Consequently, they are incapable of providing the insights in real-time that we need.

Without robust, more advanced analytics, we risk missing critical insights, trends, and opportunities for improvement in our LLM applications.

Advanced text analytics offer a competitive edge through faster and more effective iteration in line with users needs and sentiment.

Our Approach to Text Analytics at Phospho

Faster iteration and development cycles require data driven insights.

We created Phospho with a vision to help properly use text analytics to understand the market and fuel faster, more effective iteration.

We’ve catered specifically to LLM apps looking to achieve this by providing:

1. Logging: log every interaction with your LLM app in a non invasive way
2. Automatic Event Detection: define events relevant to you, Phospho then ‘flags’ them and warns you when they happen
3. Automatic Evaluation: classify the events detected as successes or failures based on your own definition
4. User Feedback: collect, attach and analyze user feedback to specific interactions
5. Review and Label: let your team annotate ‘flagged’ interactions. Collaborate with non technical team members.
6. Offline Testing: Run tests and obtain success scores BEFORE releasing your app.

If you want to understand your users closely and optimize your LLM app without siloing your nontechnical team members, sign up here and try out Phospho on your own data. It’s as simple as importing a CSV or Excel file!