DeepOpinion is a fast-growing series-A enterprise SaaS scale-up in IDP (Intelligent Document Processing) and Generative Automation, providing state-of-the-art in-house models and LLM-based automation.

DeepOpinion is a fast-growing series-A enterprise SaaS scale-up in IDP (Intelligent Document Processing) and Generative Automation, providing state-of-the-art in-house models and LLM-based automation.

Problem:

Large businesses struggle with manual workloads for repetitive cognitive tasks, leading to higher operational expenses, increased errors, and reduced productivity.

Solution

Build a generative automation and intelligent document processing platform that streamlines enterprise back-office processes, enhancing productivity by automating repetitive tasks and seamlessly integrating with existing tools and workflows. This solution reduces operational costs, minimizes errors, and improves overall efficiency, enabling businesses to focus on higher-value activities and better serve their customers.

Tools and Technologies:

Figma, Jira, Notion, HTML, CSS, React (TypeScript), Storybook, Python (FastAPI), Autotransformer (in-house model), PostgreSQL, Pinecone, GCP, LangChain, Tensorflow, GPT-4.5, Redis, Google OCR, Github, OKTA, n8n.

Established comprehensive design discipline including workflow, process...

Established a cohesive design system.

Introducing AI Copilot (AI Coworker).

Launched zero-shot and few-shot models as a node and AI skill.

Conducted user research, analysis, and root cause analysis to identify user problems.

Mapped user journeys, defined workflows, and collaborated with Trio to ideate solutions.

Designed wireframes and low-fi prototypes, ran user tests, and iterated based on feedback.

Industry

Ent. SaaS

Position

Senior Product Designer (Core Team)

Platforms

Web app

Team size

2 PD, 2 PM, 23 Eng.

Timeline

2023 - 2025

Primary User Group Persona

Aksha
Automation Developer

Age: 26

Location: Berlin

Tech Proficiency: Moderate

Gender: Male

Goal

To automate manual time-taking processes for other departments.

Performance: Easily build AI with human-level accuracy, with less data

To cut the time and increase efficiency within the BU processes

Challenges

Time: To get production ready ASAP


Reliability: To rely on the accuracy

Monitor the process status and outcomes

"I need to help other departments to automate their manual processes."

Aksha has a basic understanding of scripting languages like R and Python and brings years of experience using enterprise software. While he admires technology, he lacks the expertise to develop software independently. His approach is results-driven, with a strong emphasis on functionality and practical outcomes.

Our Process

At DeepOpinion, we adapted the double-diamond product design process. It looks something like this:

Our non-linear process reality

In reality, sometimes our process looks more like this though.

Design system development process:

Feature design discovery process

User journey map

We craft seamless user journeys by analyzing goals, optimizing interactions, and aligning workflows with user needs, ensuring efficiency and impact.

User research synthesis

To identify our users challenges, we initiate in-depth user research phases. This involved engaging with our customer base through interviews, and feedback sessions.

Usability tests

We conduct rigorous usability testing sessions to gather valuable insights and feedback from users, ensuring that the final product meets their needs and preferences while optimizing overall user experience.



SUS

Within the discovery phase, we conducted SUS (System Usability Scale) assessments by presenting users with interactive prototypes. This allowed us to gauge their ease of use, identify pain points, and gather actionable feedback to refine the design and enhance overall usability.

Problem

Users struggle to efficiently customize data processing workflows, facing challenges in adjusting pre-processing labels and defining the desired output, due to complex interfaces or the need for technical expertise.

Goal

The primary objective was to enable the users to easily adjust/create pre-processing label information and define the desirable outcome (type, format..) after the inference.

Discovery process

Method

Double Diamond

Rapid prototyping

Quantitative and qualitative research

Research result

Blind Trust in the Model: Users reported feeling uneasy relying entirely on the system without any mechanism to review or validate the model’s output.

High Error Rates: 75% of participants highlighted frequent inaccuracies in the outputs, particularly in complex or edge-case scenarios, leading to significant manual rework.

Line item processing: Users expressed interests in ways to process line items as well as line hierarchies.

Broken Feedback Loops: Participants felt disempowered because there was no way to provide feedback to improve future model performance.

No Error Indicators: The absence of indicators or explanations for potential errors in the output left users uncertain about the reliability of the results.

Research

Conducted interviews with 12 frequent users to uncover frustrations and preferences.

Analyzed behavioral data to identify bottlenecks in the current flow.

Researched competitors to identify best practices.

The Impact

The HITL interface revolutionized DeepOpinion’s document processing workflow, transforming AI-powered automation into a seamless, high-confidence experience for users in high-stakes environments.


🚀 Key Innovations:

Visual Confidence Scoring – Instantly assess AI predictions with an intuitive scoring system.

Hierarchical Labeling – Enable precise, granular data correction with structured label management.

Split-Screen Validation – Compare original documents and extracted data side by side for effortless verification.

Advanced Line-Item Validation – Validate, refine, and correct line items and their properties with precision.

Dynamic Label Editing – Modify label properties and hierarchies in real time to ensure accuracy.

AI Feedback Loops – Every correction strengthens the model, continuously improving performance and reliability.


Impact: Users in high-consequence settings gained unparalleled trust in AI automation, boosting adoption, accuracy, and efficiency in document processing like never before.

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After the consultation, we’ll provide you with a detailed plan and timeline.

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undo labs

Have a project in mind?

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Let’s talk.

Tell us about your project—whether it’s a UX/UI design, SaaS or website design and development, SEO, or marketing.

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Clear next steps.

After the consultation, we’ll provide you with a detailed plan and timeline.

Customer success

at undo labs®

Rami