Platform
From a cloud bill to a decision, in one system.
As a cloud cost intelligence startup, we built Technivex around a single cost model shared by allocation, attribution, and anomaly detection — so the number engineering sees matches the number finance reports.
Allocation
Every dollar, tied to a team
Raw cloud bills tell you what you spent. Technivex tells you who spent it — mapped to the team, product, and customer behind every line item, pulled from tags, resource metadata, and usage patterns, not a spreadsheet someone has to maintain.
- Works even where tagging is incomplete, using inferred ownership
- Shared infrastructure costs split by actual usage, not a flat percentage
- Every allocation rule is visible and editable, not a black box
Attribution
Cost tied to the outcome it produced
Knowing a service costs $40,000 a month means nothing without knowing what it's for. Technivex ties infrastructure spend to the business metric it supports — cost per transaction, per customer, per feature — so pricing and margin conversations have real numbers behind them.
- Unit economics down to cost-per-transaction, updated daily
- AI spend attributed to the model, prompt pattern, and feature calling it
- Margin erosion flagged before it shows up in a board deck
$0.014
Cost per transaction, live
Anomaly detection
Spikes caught in minutes, not at invoice time
Most teams find out about a runaway cost when the monthly bill lands — weeks after it started. Technivex watches spend in near real time and pages the right owner the moment a service breaks its normal pattern.
- Baselines learned per service, not a single blunt threshold
- Alerts route to the team that owns the resource, automatically
- Root-cause context included, not just "spend went up"
EC2 — us-east-1
+$8,420/day
OpenAI API usage
+$2,110/day
S3 data transfer
+$740/day
How it works
From connection to first report
Connect your billing accounts
Read-only integration with AWS, GCP, Azure, and your AI provider billing exports — no infrastructure access required.
Technivex builds the cost model
Spend is mapped to teams, products, and customers automatically, filling gaps where tagging is incomplete.
Anomaly detection starts watching
Baselines are learned per service within the first few days of connected data.
Reports go out where people work
Slack, email, or a shared dashboard — finance and engineering look at the same numbers.
See it against your real spend.
Connect a sandbox billing account and get a real cost model back, not a canned demo.