Discidius.
From MVP to Enterprise: Building Discidius into an Enterprise-Ready AI Startup Product
Discidius is a B2B call analytics platform built for teams that run phone-based customer support and sales. It turns call recordings into usable insights for day-to-day operations: quality work, coaching, and management decisions – without relying on manual listening.
The product sits in a space where “AI” only matters if it improves real workflows. For Discidius, that means helping teams run QA consistently, train consultants based on evidence, and give managers a clear view of what happens in conversations across teams and time.
In contact centers, the value of AI is practical: it has to support daily decisions, not just produce interesting dashboards.
The main challenge was building an AI product that works in operational reality. Discidius needed more than a technical implementation – they needed a partner who could help shape what to build, why it matters, and how it should work inside a contact center. The platform had to be useful for managers, QA teams, and training leads, not only for analysts or product demos.
At the same time, Software Things joined the project in March 2023 through a takeover from a previous development vendor. The existing product leaned heavily on emotion analytics. That direction alone did not cover the operational needs Discidius wanted to address: repeatable quality standards, coaching loops, and clear guidance for teams.
So the work combined two difficult tracks: stabilising and understanding the existing system, while executing a product pivot – from a narrow “emotion analytics” concept toward a broader platform designed for everyday QA, coaching, and performance management.
We worked as a product and technology partner – not an external team added to a backlog. From the beginning, the collaboration focused on decisions: what should become the product’s core, which capabilities should be prioritised, and how to translate business needs into features that contact center teams will actually use.
That led to a clear shift in the platform’s purpose. We helped evolve Discidius into an operational tool: a system for consistent call assessment, structured coaching, and manager oversight. Instead of “AI outputs” that look good in a demo, the product was shaped around real tasks: scoring, review, coaching actions, and repeatable standards that can be used across teams.
The initial takeover in March 2023 was part of this story, but not the headline. It was a starting point that required an audit, verification, and rebuilding selected parts to create a stable base for continuous development. With that foundation in place, Discidius could scale the product and deliver enterprise deployments in Poland and the Czech Republic.
They translate business requirements into effective technical solutions, and the communication stays open and transparent. – Erich Sikora, CEO, Discidius
The major functionalities
Smart Grade call scoring (1-100) that supports repeatable QA standards across teams
Personalised improvement suggestions that turn each reviewed call into a coaching action
Quality assessment views designed for managers and QA teams – not only for analysts
Conversation analysis that highlights recurring issues, objections, and questions across calls
Training support based on real conversations, helping teams prioritise topics that actually repeat
Alerts and monitoring for selected risks or patterns, so teams can react without listening to everything
Key features
Smart Grade as an operational QA standard
Smart Grade turns a call into a score and clear coaching directions. It supports consistency across teams and shortens the path from “review” to “what to do next”.
Manager and QA workflows built into the product
Discidius supports the way quality work happens in real teams: reviewing, comparing, calibrating, and focusing attention where it matters. It reduces the need for ad-hoc spreadsheets and manual sampling.
Insights that shape training priorities
By surfacing repeating questions and issues, the platform helps training teams stop guessing. Coaching topics are grounded in real conversations, not assumptions.
Monitoring and alerts for faster response
Selected patterns can be tracked over time, making it easier to notice changes early. Teams can react faster without increasing the amount of manual listening.
Enterprise deployment readiness
The product is delivered in a B2B model suited to larger organisations, supporting enterprise rollouts in Poland and the Czech Republic without naming end clients publicly.
Benefits for the client
A practical AI product that supports real operational work (QA, coaching, and management), not only reporting.
A partner who helps make product decisions: prioritisation, trade-offs, and turning requirements into features.
Faster alignment between business goals and implementation, reducing wasted development on low-impact ideas.
A stable foundation for continuous development, enabling predictable iteration and scaling.
A platform ready for enterprise deployments in Poland and the Czech Republic, including larger rollout expectations.
Stronger product clarity after the pivot – moving from emotion analytics toward measurable quality improvement.
decision support, priorities, trade-offs
QA, coaching, and manager workflows
rollout-ready platform for larger organisations
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If you’re building an AI product for your startup, we can help you shape it into something operational – a tool that teams will use every day, not a one-off demo.
