impak as a Pioneer in Impact Assessment

impak Analytics, is an AI-using fintech that has developed a user-friendly impact data & intelligence platform with impact assessment, scoring and rating solutions. impak Analytics is powered by its mission to help the financial sector make more sustainable decisions thanks to its impact assessment methodology based on international standards and principles such as the Impact Management Platform and the UN 17 Sustainable Development Goals.

The firm also develops impact indices using the impak Score™ and additional data from the impak database, which are essential for creating index funds and Exchange-Traded Funds (ETFs). The primary aim of impak is to steer capital towards businesses that generate positive social or environmental impacts.

Operational Challenges

Streamlining Financial Documentation Reviews

impak is currently working on improving its PDF document evaluation process for impact assessments. The existing method, which heavily relies on manual review, struggles with the vast and complex financial reports crucial for accurate assessments.

The company also faces challenges in presenting data effectively. They need a system that supports their internal operations and presents data clearly and insightfully to external stakeholders like investors. The challenge lies in designing a presentation method that accommodates diverse needs without compromising detail or clarity.

Additionally, impak aims to make complex assessment information accessible and understandable to a broad audience, including those without specialized knowledge, while still providing the depth needed by experts.

Lastly, impak is focused on improving client interactions with the provided data. The goal is to foster deeper engagement and facilitate richer discussions around the data, necessitating a user-friendly and interactive approach.


Implementing AI-Driven Automation

To address these issues, impak has implemented AI-driven automation aimed at accelerating the review process and enhancing the accuracy of evaluations. This solution uses advanced AI technologies to streamline and automate traditionally manual tasks, thereby reducing human error and increasing the efficiency of document reviews, which improves productivity and workflow in environments handling large volumes of PDF documents.

Key Implementation Steps Included

  • AI Chat Application

    The development of an AI chat tool integrated with Retrieval-Augmented Generation (RAG)* and Large Language Models (LLMs)** from AWS Bedrock. This tool is designed to improve the speed and accuracy of reviewing PDF documents by facilitating smarter, context-aware conversations about the data contained in these documents.

  • Expanding AI Conversational Capabilities and Model Support

    Enhancing the AI chat application’s capabilities allows for more personalized and in-depth discussions. This includes enabling users to select specific documents for analysis and boosting the AI’s ability to understand and discuss complex information more effectively.

  • * Retrieval-Augmented Generation (RAG) is an AI technology that enhances systems' ability to understand and respond to complex questions by searching through and utilizing relevant information from extensive data sets.

    ** Large Language Models (LLMs) are advanced AI algorithms that analyze and generate human language by learning from vast text data, enabling them to produce more natural and accurate responses.

The Outcomes

AI Chat Solution with RAG

Thanks to the integration of RAG, LLMs, AWS Bedrock, and other technologies, impak has successfully overcome the multifaceted challenges associated with complex data collection and processing.

The AI chat application facilitates dynamic, context-aware dialogues, allowing users to easily interact with the nuances of complex documents and analyses. This not only boosts internal operational efficiencies but also enhances the clarity and depth of information presented to end-users.

The dual achievement of improved operational efficiency and enhanced data clarity has significantly improved the decision-making process for investors and stakeholders, leading to better-informed investment decisions.


AI chat application with state-of-the-art LLMs
Integration with AWS Bedrock and Google Cloud Services.
Retrieval Augmented Generation (RAG) technology
Expanded AI conversational capabilities and model support

Let’s have a chat about another great project


Ready to talk about your next project?

Fill out a quick form describing your needs. You can always add details later on and we’ll reply within a day!


Strategic Planning

We go through recommended tools, technologies and frameworks that best fit the challenges you face.


Workshop Kickoff

Once we arrange the formalities, you can meet your Polcode team members and we’ll begin developing your next project.