FinOps for Amazon Bedrock
For enterprises already running on AWS, Bedrock is a natural first choice — it keeps your AI workloads within a familiar security boundary, simplifies procurement, and gives your teams access to the leading foundation models without standing up new infrastructure.
Deterra sits alongside it to make that investment easier to manage, govern, and scale responsibly.
Why We Built This
"AI is a beautiful balloon floating in the air — full of potential, but it needs a tether to be truly useful. Deterra is that tether."
The name is intentional. De — from deterministic, the idea that infrastructure your business depends on needs to behave predictably. Terra — earth, ground, the foundation everything else stands on.
We started with Amazon Bedrock because AWS has built something genuinely remarkable — and the enterprises adopting it at scale deserve an operational layer that matches that ambition. Deterra extends what Bedrock already does well by adding the financial visibility, governance controls, and attribution capabilities that enterprise adoption requires.
Cost visibility, spend attribution, team-level chargeback, and budget controls — purpose-built for Bedrock workloads.
Expanding to all enterprise AI usage — models, agents, and pipelines across the full generative AI stack.
Proactive cost optimization and the most sophisticated AI access governance layer available for enterprise.
The Opportunity
Enterprise AI adoption on AWS is moving faster than the FinOps and governance frameworks designed to support it. Deterra bridges that gap — extending native AWS capabilities with the enterprise-grade controls teams need to scale confidently.
AWS Cost and Usage Reports provide foundational billing data. Deterra extends that with team-level, application-level, and workload-level Bedrock attribution — giving finance and engineering a shared source of truth.
As enterprises scale agent-based workloads on Bedrock, teams need spend boundaries and access controls scoped at the team and workflow level. Deterra adds that governance layer on top of native AWS IAM and Bedrock permissions.
Complete Bedrock cost intelligence draws from CUR, CloudWatch, CloudTrail, and inference profile tags. Deterra assembles that picture automatically, so teams get the full view without manual data work.
What We're Building
Deterra is purpose-built to complement AWS native capabilities — connecting the data sources Bedrock already generates and turning them into the financial controls and governance frameworks enterprise teams require.
Every Bedrock API call mapped to a team, application, or project — using inference profile tags, CUR data, and CloudTrail events brought together in one place.
Automated allocation reports your finance team can actually use. Bill AI usage back to the right business unit without manual spreadsheets or end-of-month scrambles.
Narrowly scoped permissions for AI agents. Model allowlists, spend ceilings, and invocation limits per team — guardrails that don't slow engineering down.
Identify over-provisioned model tiers, expensive prompt patterns, and routing opportunities. We start with visibility and build toward automated action.
How It Works
Deterra integrates directly with your existing AWS environment — no infrastructure changes, no code modifications, no data leaving your account boundary. We work with what Bedrock already generates.
One cross-account IAM role, scoped to the minimum permissions Deterra needs. We read CUR, CloudWatch, CloudTrail, and inference profile tags — nothing beyond that.
Define your org hierarchy once. From that point on, every dollar of Bedrock spend is automatically attributed to the right team, environment, or application.
Budget thresholds, model allowlists, and agent permission scopes — configured per team. You get alerted before a budget breaks, not after the invoice arrives.
Finance gets automated chargeback reports. Engineering gets live dashboards. Leadership gets a clear picture of what AI is actually costing the business — and what to do about it.
Who It's For
Deterra is built for organizations that have moved past Bedrock experimentation and into production — where responsible AI adoption means having the same financial rigor and governance controls they apply to the rest of their cloud.
Ready to bring the same cost discipline they've built across their cloud estate to AI workloads — and looking for tooling purpose-built for Bedrock's economics.
Building and running AI workloads on Bedrock at scale, and looking for the observability and cost attribution layer that makes their work visible and accountable to the wider organization.
Committed to enterprise AI adoption done right — with the audit trails, policy controls, and compliance-ready reporting that regulated environments and board-level accountability require.
Early Access
We're working with a small group of enterprise teams running production Bedrock workloads. If that's you, we want to hear what you're running into — and show you what we've built so far.
We'll reach out personally. No drip campaigns, no automation.
✓ Got it — expect a note from us soon.