Turn AI prototypes into products people can trust
Nivara brings planning, evaluation, releases and product intelligence into one operating layer. Your team finally works from the same truth.
Trusted by forward-thinking AI teams
- Aether Labs
- Synq Systems
- HelioStack
- Cortexa
- StratosIQ
Move fast without giving up control
Enterprise-grade controls built into every layer. Your team ships faster while security and compliance stay airtight.
Plan the work worth shipping
Turn vague ideas into clear specifications. Prioritize AI features against real product goals and align your team before a single prompt is written.
86% positive
Learn from every release and improve faster
Close the loop with product intelligence that shows how features perform in the wild. Turn user feedback and live metrics into your next iteration.
- Live quality scores
- User feedback streams
- Iteration loops
One platform, four ways to see it
Every role carries a different weight. Nivara gives each one the right tool for the job.
Product
Prioritize AI features against real goals. See the full context of every release before it ships.
Engineering
Automate quality gates and staged rollouts. Ship code without the manual review death march.
AI/ML
Compare models side by side. Catch regressions before they ever touch a user.
Operations
Watch cost, latency, and adoption in real time. Keep the system running while everyone else builds.
Metrics overview
Live- Quality score
- +18%
- Latency
- 182ms
- Cost per request
- -31%
Performance trend
Latency improved
-42% in last 7 days
The numbers do not lie
Quality, cost, latency, and adoption all in one place. You see the truth before your users say a word.
- Fewer regressions caught before they reach production
- 50%
- Lower cost per request across every model you run
- 50%
Customer proof
Real teams. Real numbers. Real results.
- 5 out of 5 stars
“We cut our release cycle from eighteen days to four. Nivara gave us evidence to move fast without breaking trust.”
Sarah Chen
VP Product, Northwind
- 5 out of 5 stars
“Our engineers stopped guessing. Quality gates caught regressions before they ever reached a user.”
Marcus Webb
Head of Engineering, Lumen
- 5 out of 5 stars
“We saw cost per request drop by half. The intelligence layer paid for itself in the first month.”
Elena Rodriguez
CTO, Ardent
The next version should be easier to ship than the last
Stop losing good ideas to bad process. Give your team one operating layer and ship with evidence.