Have you ever launched something that looked solid, but users still dropped off? Everything was in place: code, tests, and deployment. But people hesitated, left early, or never engaged.
Observability helps your whole team, devs, QA, UX, and product, see what’s really going on, so you can build with clarity and act with purpose.
Let’s make your data work for you!
Your team works fast, and features ship often, but the feedback loop is usually slow or unclear. By the time someone reports a problem, the trail is already cold.
Observability shortens that gap. It gives you context when something feels off, but nothing looks broken. Instead of searching blindly, you start with real signals: usage patterns, behavior shifts, performance clues. You move from reacting to understanding.
In-depth observability brings that clarity into your workflow, across development, testing, and operations.
Not everything gets caught in testing.
We connect functional tests with real-world behavior to highlight the gaps: flows that matter but aren’t covered, bugs that only appear under certain conditions, issues that grow quietly.
A product can pass load tests and still feel slow.
We show you how it performs for real users, in real conditions. That includes layout shifts, delays in key elements, and interactions that create friction even when technically correct.
Not all blockers are bugs.
We help UX teams surface friction points like hesitation, confusing copy, or abandoned flows. With observability, you get insight into how people actually move through your product, so every interaction can feel smoother and more intentional.
Different teams see different pieces. Observability brings them together.
We help QA, dev, product, and design share the same view of what’s happening, so they can make better decisions, faster, and with fewer handoffs.
Fixing issues in production is costly.
We integrate observability into your CI/CD pipeline so you detect regressions and inconsistencies before they reach users. Our approach combines shift-left & shift-right testing.
Too many alerts slow you down, whereas insight moves you forward.
With Abstracta Copilot, we use AI to spot patterns in logs, traces, and tests. It flags what’s relevant, so your team can dig into what actually needs attention.
LLMs often behave unpredictably.
In AI products, especially with black box models, observability helps uncover unexpected outputs. With custom tools and AI Agents, we bring visibility and accountability into machine learning pipelines.
Together with Datadog, we help you monitor, secure, and optimize every layer of your cloud infrastructure, without slowing down delivery.
From custom dashboards to team-specific alerting, we tailor Datadog to your reality. So you don’t just see more, but what matters.
If you’re running blind in key moments, you’re not alone. We’ve helped teams like yours turn confusion into clarity, with tools, practices, and a real partner to guide the way.
Tell us what you’re trying to understand better. We’ll help you find the signals that matter.
