Meridian AI FinOps

Now Generally Available — Enterprise AI Governance & FinOps

Your AI outcomes are running out of control. Meridian keeps them governed.

The Enterprise AI Control Plane. One gateway across every agent, MCP server and model, governing quality, performance and cost - continuously.

Always-on

Quality evals against baseline

of requests timed and tagged

0-0%

lower cost with Intelligent Routing or General Symbolic Reasoning

1wk

to full spend attribution

The Problem

AI has left the pilot phase. The operating model hasn't caught up.

Cloud and Data have mature governance frameworks. AI has none that governs quality, performance and cost together. Today, managing one means trading away another.

Cut cost, and quality erodes

Teams default to premium models. Cheaper models save money, but quality can slip, and without a baseline nobody notices until a user does.

15-25%

less accurate without reasoning mode (2025 benchmark)

Raise quality, and performance degrades

Longer reasoning lifts quality but adds tokens, latency and rework. Many organizations have no latency target or clear owner for the experience.

longer to restore that accuracy (2025 benchmark)

Runaway, unattributed spend

API calls, MCP servers, coding agents and AI-enabled SaaS fall outside cloud billing until the invoice arrives. Finance cannot charge back what it cannot see.

50%+

of GenAI projects overrun budgets through 2028 (Gartner)

Long tasks compound every trade-off

Agents chain many steps, and small errors compound. Most multi-step tasks hit an error, and retries add delay and spend.

>30%

Likelihood of multi-step tasks failing

The Solution

The Enterprise AI Control Plane

Meridian governs quality, performance and cost together through a single gateway, without changing how your teams build. It instruments every request, measures all three, makes spend visible and optimizes continuously.

Instrument

Every request captured and tagged, automatically.

Measure

Quality, performance and cost, down to a single request.

Visualize

One dataset, a dashboard per audience.

Optimize

Six levers, applied only where they pay off.

Gateway

One endpoint, every provider

One endpoint to OpenAI, Anthropic, Google, Azure, AWS Bedrock and 100+ others, scoped to an approved-model allowlist. Virtual keys with spend caps and auto-revoke. MCP and A2A support built in.

Optimization

Six levers, two that go further.

Model right-sizing, prompt caching, semantic caching and context compression are built in. Datacolor Intelligent Routing evaluates quality before a switch is trusted. Datacolor General Symbolic Reasoning (GSR) plans complex, long-horizon tasks before the model runs.

Governance

Governance, enforced on every request

Configurable guardrails screen every request for PII and prompt injection, then block or mask it before it reaches a provider. Policies set which model families each project, team or role can use, with budgets and spend caps enforced before spend happens. Every decision is logged for audit, with SIEM-ready exports.

Integration

Change the endpoint.  Nothing else.

Most integrations complete in under 4 hours. No agent
re-architecture. No prompt re-work. No new infrastructure.

Framework-agnostic

OpenAI-compatible API

VPC & on-prem capable

Air-gapped deployment

Kickoff and baseline

Datacolor engineers capture your current spend baseline within 24 hours of kickoff. No agent code changes, no security review required.

Instrument your estate

The gateway is configured for your model × cloud combinations. Agent metadata model maps costs to departments and accounting codes.

Activate optimization levers

Routing, Context Compression and Semantic Caching activate first for immediate impact. Eval-based Routing and GSR activate on your highest-spend agentic workloads.

Deliver a defensible ROI number

A measured before-and-after comparison on your real workloads. Finance-ready chargeback from day one.

Business Outcomes

What you actually get

Eight outcomes that balance quality, performance and cost. Each attributable. Each measurable within your first 30 days.

Full visibility

Every request attributed to its team, project, user, model and environment, with quality, latency and cost scored together.

Quality you can prove

Always-on evals against your baseline show whether a cheaper or faster model holds your quality bar, before and after every change.

Performance you can plan around

Every request is timed and tagged, so latency is tracked by model and workload, and speed against cost becomes a choice you make.

Lower cost, same quality bar

Datacolor Intelligent Routing or Datacolor General Symbolic Reasoning lowers cost 30% to 50%, checked against your quality baseline.

Complex work done right

Datacolor General Symbolic Reasoning keeps long-horizon agent tasks on plan, with an execution trace your team can review.

Predictable spend

Budgets, hard-stop limits and real-time alerts prevent runaway spend. Finance gets reliable monthly forecasts.

Responsible agent scaling

Roll out coding agents and custom agents across hundreds of engineers with budgets, guardrails and model policies from day one.

Governed by design

Guardrails for PII and prompt injection, model-family allowlists by project and role, and an audit trail for security reviews.

Competitive Position

Why Meridian is different

Observability platforms tell you what happened after it happened. BI dashboards describe the spend without changing it. Cloud FinOps tools weren't built to understand tokens, model tiers or agents. Meridian is the control point - and the only peer-reviewed reasoning layer on the market.

Capability

Point Solutions

Meridian

Full spend attribution

Built for specific use cases

Enterprise-wide, 100% coverage

Continuous quality measurement

Not tracked systematically

Per call, against your evals

Continuous eval-based routing

Static rule sets, rarely revisited

Self-relearning, per task

Neuro-symbolic GSR layer

Generally not offered

A differentiated, purpose-built layer

Semantic caching

Typically exact-match only

Semantic, higher hit rates

Finance chargeback-ready

Usually needs export to BI tools

Native, finance-ready on day one

Peer-reviewed benchmarks

Vendor-reported

Published and peer-reviewed

Six optimization levers together, an industry-first

Leverage Model right-sizing, Prompt Caching, Semantic Caching, and Context Compression almost across all use-cases. Bundled with Continuous eval-based Intelligent Routing and Datacolor GSR for curated optimization across priority use-cases.

Visibility first, then defensible optimization

Meridian establishes a measured baseline before activating any optimization lever. Every savings claim is backed by a before-and-after comparison on your real workloads - not vendor projections.

One thin layer. Zero re-architecture.

Agent architecture, prompts, tool definitions, and downstream consumers remain completely unchanged. The entire estate - direct APIs, cloud-hosted models, coding agents - captured through a single, provider-agnostic gateway hop.

Built for Finance, not just Engineering

The agent metadata model produces chargeback reports Finance can actually post. AI cost becomes a first-class financial metric - not a quarterly retrospective where the number is already locked.

The Business Case

Measured on your workloads

The business case is built on your own workloads, not industry averages. Quality, performance and cost are measured together, so every saving is checked against your quality bar.

30-50%

Lower cost with either lever

With Datacolor Intelligent Routing or Datacolor General Symbolic Reasoning, against direct model use on your own production workloads.

Always-on

Quality evals

Every optimization is scored against your quality baseline, so savings never come from quietly lowering the bar.

100%

Of requests timed and tagged

Latency, tokens and cost captured for every request, by project, team and model. No agent code changes.

Nearly 70%

Lower cost per successful outcome

With all six levers combined: four built in, plus Datacolor Intelligent Routing and Datacolor General Symbolic Reasoning.

2 weeks

Proof of value

Run Meridian on your workloads and see measured quality, performance and cost before you commit.

Advisory Board

AI industry leaders and academic experts

Meridian's product direction is shaped by practitioners who have built and operated AI infrastructure at scale - from enterprise software leaders to the researchers who published the benchmarks it runs on.

Priya Reddy

Founder & CEO, AI & Data Strategy & Innovation

Priya Reddy Consulting

"Turning startup chaos into enterprise credibility requires the kind of AI cost visibility that Meridian delivers - the boardroom finally has numbers it can trust."

Babar Bhatti

Chief AI Officer

Prism

"Building AI-augmented organizations means making every LLM investment accountable. Meridian is the control layer that makes that possible at scale."

Colin Hare, Ed.D.

EVP & Global Practice Lead: Analytics & Growth Consulting

Circana

"Enterprise AI governance starts with knowing where every dollar goes. Meridian gives analytics and consulting leaders the spend attribution they've been missing."

Arjun Srinivasan

SVP - AI & Data Science

ShipStation Global

"Technology strategy means nothing without financial discipline. Meridian brings FinOps rigor to the AI estate that every data and AI executive needs right now."

Dr. Ashim Bose

Professor in Naveen Jindal School of Management, UT Dallas

Former SVP & GM Data, Analytics, AI in RealPage, Inc

"Becoming AI-first demands more than adopting models - it demands operational discipline over cost, quality, and governance. Meridian is the infrastructure that enables that discipline."

Customer Outcomes

What early adopters are seeing

35% quality gain

on multi-step document processing

The quality improvement on multi-step document processing, without touching our agent code, was unexpected. $2.1M of annualized AI spend is now under governance alongside it.

Head of AI COE

PE-backed Healthcare Group

$190K

in savings per quarter, across multiple workload types

We started with a single workload. Once it matched frontier-model quality at roughly a third of the cost, we expanded to features, PRs, functions and agent runs, all on the same optimization layer.

VP of Engineering

Leading Mortgage Industry Firm

6 mo → 2 wks

to finance-ready chargeback

Finance had asked for AI cost chargeback for six months. Meridian gave them a report they could post against budget codes.

Chief Data Officer

Mid-Market Financial Services

How to Engage

Prove it on the workload that matters most.

Start with a 2-week POC on your highest-value workload. Measure twice-baseline, then with Meridian-holding quality constant while cost moves, for a defensible number.

Week 1

Instrument and baseline

The gateway is configured for your top model × cloud combinations. Attribution is live by end of week one.

Week 2

Activate and measure

Routing, caching and GSR activate on your highest-spend workloads, then re-run for a defensible delta.

Beyond Week 2

Production and governance

Deployment in your VPC or on-prem, air-gapped capable. Always-on quality, anomaly and budget governance.

Start your 2-week POC

→ Baseline results within 24 hours of kickoff

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