StackTrack
Now in development — Early access coming soon

The intelligence layer for enterprise technology spend

StackTrack replaces spreadsheet-driven IT budgeting with AI-powered, driver-based forecasting across your entire technology portfolio — SaaS, cloud, AI inference, security, and infrastructure.

$6.15T
Global IT Spend 2026
98%
Enterprises Managing AI Spend
30%
AI Cost Underestimation
The Problem

Technology is one of the largest enterprise expenses. The forecasting is still done in spreadsheets.

Organizations spend millions on technology every year, yet the tools for forecasting and managing that spend have not evolved in decades.

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Fragmented Visibility

SaaS contracts in one spreadsheet, cloud bills in another, AI inference costs buried in engineering dashboards. No unified view exists.

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No Predictive Models

Finance teams forecast technology costs using last year's numbers plus a growth factor. That breaks when headcount shifts, workloads spike, or AI adoption accelerates.

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Surprise Renewals

Contract renewals with automatic escalators catch teams off guard. By the time they notice, the negotiation window has closed.

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AI Cost Blindspot

AI inference, tokens, and agent compute are now the fastest-growing cost category in enterprise tech — and nobody has a forecasting model for it.

The Platform

One platform. Every technology dollar. Predictive intelligence.

StackTrack ingests and normalizes messy technology cost data using AI, extracts the billing drivers behind each service, and models how costs evolve based on real business metrics.

Ingestion

AI-Powered Data Normalization

Ingest billing data from any source — SaaS invoices, cloud consoles, vendor contracts, AI API billing, security tools. StackTrack normalizes it all into a unified taxonomy automatically.

Forecasting

Driver-Based Forecasting

Model how costs evolve based on headcount growth, workload scaling, revenue shifts, and contract renewals — not static budget lines.

Renewals

Renewal Impact Modeling

Track every contract renewal with utilization data, risk scoring, and optimization signals. Know which renewals to renegotiate months before auto-renewal kicks in.

Scenarios

Scenario Analysis

Model baseline, growth, and contraction scenarios across your entire technology portfolio. See how hiring plans, market shifts, and vendor changes impact your budget in real time.

Intelligence

Proactive AI Insights

Surface vendor overlap, underutilized licenses, approaching tier thresholds, and cost anomalies before they become budget problems.

Unified View

Single Pane of Glass

SaaS, cloud, AI, security, infrastructure, telecom — every technology dollar in one platform with consistent taxonomy, forecasting, and governance.

AI Spend Intelligence Module

AI inference, tokens, and agent workloads are now the fastest-growing and least predictable cost category in enterprise technology. StackTrack's AI Spend Intelligence module brings the same forecasting discipline to AI costs that the platform delivers for SaaS and cloud.

AI Cost Ingestion

Pull billing data from OpenAI, Anthropic, Azure OpenAI, Bedrock, Vertex AI, and AI gateway telemetry into a unified view.

Token-Level Forecasting

Model AI costs based on inference volume, model mix, agent sessions, and workload scaling — drivers that don't exist in traditional budgeting.

Governance Visibility

Shadow AI discovery, team-level cost attribution, ROI analysis by use case, and committed-use threshold alerts.

Value Quantification

Connect AI spend to business outcomes. Answer the question every CFO is asking: is our AI investment delivering value?

How It Works

From messy data to predictive intelligence in four steps.

01

Connect Your Data

StackTrack integrates with your cloud billing consoles, SaaS vendor portals, contract management systems, and AI provider APIs. Setup takes hours, not months.

02

AI Normalizes Everything

Our AI engine classifies, categorizes, and normalizes your cost data — extracting the billing drivers behind each service and mapping them to your business metrics.

03

Forecast With Confidence

Driver-based models project your technology costs based on how your business actually operates. Scenario analysis shows what happens when plans change.

04

Act on Intelligence

Proactive alerts surface renewal risks, optimization opportunities, vendor overlap, and budget variances — giving you time to act before costs become surprises.

Market Context

The market is moving. The tools have not kept up.

Enterprise technology spending is at an all-time high, AI costs are exploding, and legacy budgeting tools were never built for this complexity.

$6.15T
Global IT spending in 2026 — growing 10.8% year over year
Gartner, 2026
98%
Of organizations now manage AI spend — up from 31% just two years ago
FinOps Foundation State of FinOps 2026
30%
Projected rise in underestimated AI infrastructure costs at G1000 companies
IDC FutureScape 2026
$4.3B
IBM's acquisition of Apptio — validating the tech spend management category
IBM, 2023
The Team

Built by operators who have lived the problem.

Domain Expertise Meets Engineering Excellence

StackTrack is built by IT operations veterans who spent years managing technology budgets inside the enterprise. We did not read about this problem in a market report — we lived it. Every feature in the platform exists because we needed it and it did not exist.

Our founding team combines deep ITAM and technology operations expertise with the engineering capability to build an AI-native platform from the ground up.

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Deep Domain Expertise

15+ years managing technology spend, vendor relationships, and IT asset management inside enterprise organizations.

Technical Foundation

Engineering leadership with experience building scalable data platforms, AI/ML pipelines, and enterprise SaaS applications.

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Enterprise Network

Direct relationships with CIOs, CFOs, and FinOps practitioners who are the buyers of this platform.

Get early access to StackTrack.

We are onboarding design partners now. If you are managing technology spend across SaaS, cloud, AI, and infrastructure — and tired of doing it in spreadsheets — we would love to talk.