The Agent Stack: AI Spend & ROI

10 Companies 4 Categories The Agent Stack

This landscape covers startups that help companies understand and control the economics of AI systems and agents. These products show where AI spend comes from and whether that spend creates enough business value.

Filter and ordering

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Category

AI Cost Attribution

2 companies

Software that shows which agent, workflow or product generated a given AI cost. The goal is to make spend traceable to the work that caused it.

AgentCost

agentcost.tech

AgentCost is an open source cost observability tool for AI systems that attributes LLM spend to the agent, workflow, project, or model that caused it.

unknown Employees Bootstrapped Stage 2025 Founded

Trajectory Maturity Level Nascent

Confidence: Medium

FinOps LLM

finopsllm.com

FinOps LLM helps teams attribute and govern LLM and GenAI spend so they can trace costs back to the workloads, teams, or features that caused them.

unknown Employees Unknown Stage 2026 Founded

Trajectory Maturity Level Nascent

Confidence: Low

Category

Runtime Spend Control

3 companies

Software that applies spending rules while AI systems are running. It can stop or limit activity when usage crosses an economic threshold.

AI SpendOps

aispendops.com

AI SpendOps builds a proxy based platform that tracks AI usage, attributes cost, enforces spend policies, and produces finance grade reporting for AI API calls.

Total employee count undisclosed; Companies House lists one active director Employees Unknown Stage 2026 Founded

Trajectory Maturity Level Nascent

Confidence: Medium

Kosmoy

kosmoy.com

Kosmoy is an AI management platform that gives enterprises a gateway, monitoring, and runtime control layer for LLMs and agents, including spend caps that can stop calls when budgets are reached. ([kosmoy.com](https://www.kosmoy.com/?utm_source=openai))

11-50 Employees Unknown Stage 2023 Founded

Trajectory Maturity Level Early

Confidence: Medium

Tokenomy

tokenomy.ai

Tokenomy builds runtime FinOps software for AI systems. It meters AI usage, enforces budgets and policies before spend happens, and helps teams attribute and control model cost as systems run.

unknown Employees Unknown Stage 2025 Founded

Trajectory Maturity Level Nascent

Confidence: Medium

Category

AI ROI & Unit Economics

3 companies

Software that compares AI spend with the business outcome it produces. It helps companies understand whether an agent or workflow creates enough value to justify its cost.

Ascerta

ascerta.com

Ascerta makes software that measures AI cost, adoption, and business value so enterprises can tell which AI initiatives are worth scaling.

11-50 Employees Series A Stage 2024 Founded

Trajectory Maturity Level Early

Confidence: Medium

Husk

usehusk.com

Husk is a finance platform that helps startups and growing teams manage company spending, cash flow, and AI spend economics with cards, controls, and real time insights.

2 to 10 employees Employees Pre Seed Stage 2023 Founded

Trajectory Maturity Level Early

Confidence: Medium

Cogs'z

cogsz.com

Cogs'z is a cloud software platform that helps SaaS and AI companies track profitability, allocate costs, and measure AI spend against business outcomes.

2-10 Employees Unknown Stage 2022 Founded

Trajectory Maturity Level Nascent

Confidence: Low

Category

Cost Optimization & Routing

2 companies

Software that reduces AI costs by changing how work is executed. It selects cheaper execution paths when they can deliver an acceptable result.

FinChop

finchop.io

FinChop is a private beta platform that reduces AI spend by routing each task to the lowest cost model that can still meet quality needs and by showing ROI across workflows.

unknown Employees Unknown Stage Unknown Founded

Trajectory Maturity Level Nascent

Confidence: Low

Tokenistt

tokenistt.com

Tokenistt is an AI FinOps platform that helps enterprises track, govern, and reduce LLM spend by routing requests across providers and optimizing execution paths.

5-person founding team Employees Pre Seed Stage Unknown Founded

Trajectory Maturity Level Nascent

Confidence: Medium

The Agent Stack: AI Spend & ROI competitive landscape summary

The Agent Stack: AI Spend & ROI contains 10 companies across 4 categories. This landscape covers startups that help companies understand and control the economics of AI systems and agents. These products show where AI spend comes from and whether that spend creates enough business value.

AI Cost Attribution

Software that shows which agent, workflow or product generated a given AI cost. The goal is to make spend traceable to the work that caused it.

AgentCost

Website: agentcost.tech

AgentCost is an open source cost observability tool for AI systems that attributes LLM spend to the agent, workflow, project, or model that caused it.

Category: AI Cost Attribution. Funding stage: Bootstrapped. Founded: 2025. Employees: unknown.

Landscape fit: It fits AI cost attribution because the core product traces LLM calls to the specific agent or workflow that generated the cost and shows spend breakdowns by agent, project, and model.

Company timeline

2026-10-04: HR snapshot (hr) . AgentCost identifies Kushagra Agrawal as founder and maintainer and offers direct founder contact. The supplied evidence does not establish headcount or active job openings. Source: About AgentCost. https://agentcost.tech/about
2026-10-04: Product snapshot (product) . AgentCost describes an open-source LLM cost observability platform with a Python SDK, analytics dashboard and API, budget controls, reports, local analysis CLI, model catalog, MCP tools, and self-hosted deployment. Source: About AgentCost. https://agentcost.tech/about
2026-10-01: Free cloud pricing launches (gtm) . AgentCost positioned its hosted cloud as free and said self hosting is optional. Source: AgentCost pricing page. https://agentcost.tech/pricing
2026-09-08: Per-agent analytics pages released (product) . AgentCost added dedicated agent pages and an Agents list with spend changes, trends, cost per run information, and guardrail state. Source: Changelog | AgentCost. https://agentcost.tech/changelog
2026-09-05: Per-agent guardrails and compliance view released (product) . AgentCost added a Guardrails page for per-agent boundaries, compliance checks, and breach notifications. Source: Changelog | AgentCost. https://agentcost.tech/changelog
2026-08-11: AgentCost adds workflow tracing and pre-deployment cost analysis (product) . AgentCost released workflow-level cost tracing, cost per completed outcome, and a local pre-deployment analyzer that can flag expensive agent behavior before production. Source: AgentCost changelog. https://agentcost.tech/changelog

FinOps LLM

Website: finopsllm.com

FinOps LLM helps teams attribute and govern LLM and GenAI spend so they can trace costs back to the workloads, teams, or features that caused them.

Category: AI Cost Attribution. Founded: 2026. Country: United States. Employees: unknown.

Landscape fit: It fits AI cost attribution because the product is built to reconcile invoices and usage data, assign spend to the responsible workload, and make AI costs traceable at the request and team level.

Company timeline

2026-10-04: Verified savings pricing (gtm) . FinOps LLM prices implementation and optimization as a share of verified monthly savings. The pricing page also sets a minimum managed engagement of $20,000 per month in LLM spend. Source: Pricing · FinOps LLM. https://finopsllm.com/pricing
2026-10-04: HR snapshot (hr) . The careers page states that there are no open roles and no standing headcount plan. It invites targeted outreach and mentions possible contract or advisory work. The supplied evidence does not establish headcount. Source: Careers · FinOps LLM · No Open Roles, Notes Welcome. https://finopsllm.com/careers
2026-10-04: Free audit motion (gtm) . FinOps LLM offers a free, human led audit that starts from read only billing and usage data. The booking flow positions the audit as the entry point to an implementation engagement. Source: Book · FinOps LLM. https://finopsllm.com/book
2026-10-04: Product snapshot (product) . FinOps LLM describes managed AI cost management and LLM observability, including invoice reconciliation, token-level attribution, anomaly detection, chargeback/showback, routing, caching, and compression. Tidal Telemetry provides hosted LLM traces and usage reporting as a separate beta product. The website also hosts a public AI model release tracker. Source: FinOps LLM - AI cost management for the era of tokens. https://finopsllm.com
2026-10-04: AI model release tracker shipped (product) . FinOps LLM launched a public page for tracking new GPT and Claude model releases. It is a distinct public tool rather than a general research article. Source: AI Model Release Tracker: New GPT & Claude Models · FinOps LLM. https://finopsllm.com/tools/llm-release-tracker
2026-10-03: No open roles (hr) . FinOps LLM says it has no open roles and no standing headcount plan. It still invites targeted outreach for relevant experience and possible contract or advisory work. Source: Careers · FinOps LLM · No Open Roles, Notes Welcome. https://finopsllm.com/careers

Runtime Spend Control

Software that applies spending rules while AI systems are running. It can stop or limit activity when usage crosses an economic threshold.

AI SpendOps

Website: aispendops.com

AI SpendOps builds a proxy based platform that tracks AI usage, attributes cost, enforces spend policies, and produces finance grade reporting for AI API calls.

Category: Runtime Spend Control. Founded: 2026. Country: United Kingdom. Employees: Total employee count undisclosed; Companies House lists one active director.

Landscape fit: It fits runtime spend control because its proxy sits between applications and AI providers, and it can enforce policies, track usage, and alert on or limit budget use while requests are running.

Company timeline

2026-10-04: HR snapshot (hr) . Companies House lists one active director for AI SPENDOPS LTD. This is not evidence of total employee count. No clear public hiring signal is established by the supplied evidence. Source: AI SPENDOPS LTD people. https://find-and-update.company-information.service.gov.uk/company/17046015/officers
2026-10-04: Product snapshot (product) . AI SpendOps is a proxy-based AI spend management platform. Its official website and documentation describe usage tracking, cost attribution, policy enforcement, budget alerts, and reporting for AI API calls. Source: official website. https://www.aispendops.com
2026-10-01: Self serve access announced (gtm) . AI SpendOps says the service is available to customers in the United States and worldwide, with self serve signup available. Source: FAQ. https://www.aispendops.com/faq
2026-09-01: LLM gateway comparison published (gtm) . AI SpendOps published a comparison of LLM gateways and placed its product in the cost attribution and governance category. Source: The Best LLM Gateways in 2026, Sorted by the Job You Need Done. https://www.aispendops.com/blog/best-llm-gateways-2026
2026-08-01: Vercel AI Gateway support added (product) . AI SpendOps announced support for Vercel AI Gateway. Teams can route traffic through AI SpendOps in front of the gateway for cost attribution, budgets, and governance while keeping the existing gateway key. Source: AI SpendOps Now Supports Vercel AI Gateway. https://www.aispendops.com/blog/vercel-ai-gateway-support
2026-08-01: Budget alerts launched (product) . AI SpendOps announced budget alerts as live for all plans. Budgets can be scoped to an organisation, API key, provider, or dimension value, with email warnings at configured thresholds. Source: Budget Alerts Are Now Live in AI SpendOps. https://www.aispendops.com/blog/budget-alerts-now-live

Kosmoy

Website: kosmoy.com

Category: Runtime Spend Control. Funding stage: . Founded: 2023. Country: Italy. Employees: 11-50.

Landscape fit: It fits runtime spend control because it enforces budgets and can block AI calls at the gateway while systems are running. ([kosmoy.com](https://www.kosmoy.com/platform/ai-finops/?utm_source=openai))

Company timeline

2026-10-04: HR snapshot (hr) . Kosmoy is identified on its official company page as led by CEO Umberto Malesci. The supplied Crunchbase summary lists 11–50 employees, but no observation date is supported. A backend engineering job posting provides evidence of a role, not a reliable current hiring count. Source: About Kosmoy. https://www.kosmoy.com/company
2026-10-04: Product snapshot (product) . Kosmoy publicly describes an enterprise AI management platform with an AI Gateway, Mission Control for agent fleets, and Action Capsule runtime containment. The supplied material supports these as described capabilities, but does not establish launch dates for them. Source: Enterprise AI Gateway page. https://www.kosmoy.com/platform/ai-gateway
2026-09-01: Kosmoy adds agent cards and AI BOM (product) . Kosmoy introduced agent cards and an AI BOM schema to describe and track AI agents more formally. The material positions the feature as a governance and inventory layer. Source: Agent Cards and AI BOM. https://www.kosmoy.com/resources/blog/agent-cards-ai-bom
2026-09-01: Kosmoy adds agent registry and discovery (product) . Kosmoy published material on discovering unregistered AI agents and maintaining a master agent registry. The company tied the theme to governance and oversight workflows. Source: Agent Discovery: How to Find Unregistered AI Agents. https://www.kosmoy.com/resources/blog/agent-discovery-shadow-agents
2026-08-28: Kosmoy publishes enterprise comparison guides (gtm) . Kosmoy’s blog index shows buyer guides and vendor comparisons aimed at enterprise AI middleware and governance evaluation. The content is explicitly commercial and meant to shape buying decisions. Source: Blog — Kosmoy. https://www.kosmoy.com/resources/blog
2026-08-14: Kosmoy adds runtime containment (product) . Kosmoy described Action Capsule as a Kubernetes native sandbox for autonomous AI agents. The material emphasized controlled egress and runtime containment. Source: Kosmoy Action Capsule: Runtime Containment for Autonomous AI Agents. https://www.kosmoy.com/resources/blog/action-capsule-ai-agent-containment

Tokenomy

Website: tokenomy.ai

Tokenomy builds runtime FinOps software for AI systems. It meters AI usage, enforces budgets and policies before spend happens, and helps teams attribute and control model cost as systems run.

Category: Runtime Spend Control. Founded: 2025. Country: United States. Employees: unknown.

Landscape fit: It fits runtime spend control because the product is explicitly built to enforce budgets, routing, and circuit breakers in the request path while AI is running.

Company timeline

2026-10-04: HR snapshot (hr) . The official about page names Mahesh Lambe as founder. No employee count or verifiable active hiring openings are established by the supplied fetched text. Source: About & Team. https://www.tokenomy.ai/about
2026-10-04: Product snapshot (product) . Tokenomy describes an AI spend control and runtime FinOps platform for LLM and agent workloads. The supplied official materials describe metering, budget controls, routing, caching, chargeback, invoice runs, API access, and research and free-tool offerings. Source: Tokenomy homepage. https://www.tokenomy.ai
2026-09-01: Tokenomy publishes AI economics academy (product) . Tokenomy launches an academy surface for AI economics education. Source: AI Economics Academy. https://tokenomy.ai/academy
2026-09-01: Tokenomy publishes security posture (product) . Tokenomy adds a trust page that presents its security and compliance posture for the runtime product. Source: Trust, security and compliance. https://www.tokenomy.ai/trust
2026-09-01: Tokenomy opens public pricing (product) . Tokenomy publishes paid pricing tiers on its official pricing page. Source: Pricing page. https://www.tokenomy.ai/pricing
2026-09-01: Tokenomy adds API access (product) . Tokenomy’s API access page describes a key for live and historical model prices and authentication for the metering runtime. Source: API Access. https://www.tokenomy.ai/api-access

AI ROI & Unit Economics

Software that compares AI spend with the business outcome it produces. It helps companies understand whether an agent or workflow creates enough value to justify its cost.

Ascerta

Website: ascerta.com

Ascerta makes software that measures AI cost, adoption, and business value so enterprises can tell which AI initiatives are worth scaling.

Category: AI ROI & Unit Economics. Funding stage: Series A. Founded: 2024. Country: United States. Employees: 11-50.

Landscape fit: It fits AI ROI and unit economics because the product is built to connect AI usage and cost to measurable business value, so teams can judge whether an agent or workflow earns its keep.

Funding rounds

Series A announced 2026-09-30 : 18100000 USD ; investors: Dell Technologies Capital, Hitachi Ventures, Wipro, BGV, Gaia Ventures, FUSE, Tola Capital ; source: The Journey to Series A | Ascerta ; https://ascerta.com/resources/blogs/the-journey-to-series-a
Seed announced 2025-05-01 : 4900000 USD ; source: Ascerta raises $18M Series A to help enterprises maximize AI ROI ; https://ascerta.com/resources/press/ascerta-raises-18m-series-a

Company timeline

2026-10-04: HR snapshot (hr) . No sufficiently verified employee-count or recruiting signal is available from the supplied evidence. Source: HR source.
2026-10-04: Product snapshot (product) . Ascerta presents an enterprise platform for analyzing AI costs and activity and relating AI use cases to business value. Its materials describe use-case and KPI tracking, AI adoption and capacity analysis, and coding-agent activity insights. Source: Ascerta home page. https://ascerta.com
2026-09-30: Customer savings case (gtm) . GeekWire reported a customer example in which Ascerta helped an insurer cut capacity costs. Source: GeekWire. https://www.geekwire.com/2026/pay-i-rebrands-as-ascerta-and-raises-18m-to-help-enterprises-track-ai-business-value
2026-09-30: Series A (funding) . Amount: USD 18.1M. Investors: Dell Technologies Capital, Hitachi Ventures, Wipro, BGV, Gaia Ventures, FUSE, Tola Capital Source: The Journey to Series A | Ascerta. https://ascerta.com/resources/blogs/the-journey-to-series-a
2026-09-17: Pay-i becomes Ascerta (product) . The company said it changed its name from Pay-i to Ascerta and broadened its platform beyond AI cost management. Source: We're Now Ascerta | The Next Chapter for Pay-i. https://ascerta.com/resources/blogs/pay-i-is-now-ascerta
2025-05-01: Seed (funding) . Amount: USD 4.9M Source: Ascerta raises $18M Series A to help enterprises maximize AI ROI. https://ascerta.com/resources/press/ascerta-raises-18m-series-a

Husk

Website: usehusk.com

Husk is a finance platform that helps startups and growing teams manage company spending, cash flow, and AI spend economics with cards, controls, and real time insights.

Category: AI ROI & Unit Economics. Funding stage: Pre Seed. Founded: 2023. Country: Belgium. Employees: 2 to 10 employees.

Landscape fit: It fits AI ROI and unit economics because the product is built to show what spend is driving value, compare costs against outcomes, and help teams control or justify AI related spending.

Funding rounds

Pre-seed announced 2025-05-27 : 1000000 EUR ; investors: Techstars, Birdhouse Ventures, NewSchool.vc, angel investors ; source: Husk ; https://www.usehusk.com/blog/husk-raises-eu1m-pre-seed-to-expand-its-growth

Company timeline

2026-10-04: HR snapshot (hr) . Husk's LinkedIn company page reports 2–10 employees. Its careers page says there are no open roles right now. Source: Husk LinkedIn company page. https://www.linkedin.com/company/usehusk
2026-10-04: Product snapshot (product) . Husk's current public product scope includes corporate debit and virtual cards, card and spending controls, expense management, transaction and cash-flow insights, and AI spend visibility. Bill pay is shown as coming soon. Source: Husk home page. https://www.usehusk.com
2025-12-01: WhatsApp receipt matching (product) . Husk launched a receipt matching flow through WhatsApp. Users can send a receipt photo to Husk, which identifies the transaction and posts the matched expense to the dashboard. Source: Husk blog. https://www.usehusk.com/blog/whatsapp-receipt-matching
2025-05-27: Husk raises €1M pre-seed (funding) . Husk closed a €1M pre-seed round to expand its financial platform for European startups. Source: Husk. https://www.usehusk.com/blog/husk-raises-eu1m-pre-seed-to-expand-its-growth
2025-02-01: First dedicated sales role (hr) . Husk posted a Brussels based Sales Development Representative role and described it as its first dedicated sales representative position. Source: Husk sales development representative job. https://be.linkedin.com/jobs/view/sales-development-representative-at-husk-4299973833
2025-02-01: First customers and sales hire (gtm) . Husk said it had launched its product and onboarded its first customers while hiring its first dedicated sales representative. Source: Husk sales development representative job. https://be.linkedin.com/jobs/view/sales-development-representative-at-husk-4299973833

Cogs'z

Website: cogsz.com

Cogs'z is a cloud software platform that helps SaaS and AI companies track profitability, allocate costs, and measure AI spend against business outcomes.

Category: AI ROI & Unit Economics. Founded: 2022. Country: United States. Employees: 2-10.

Landscape fit: It fits this category because it is software for measuring AI spend and unit economics, which directly supports AI ROI and margin analysis for customers.

Company timeline

2026-10-04: HR snapshot (hr) . The fetched evidence does not verify employee count or current recruiting activity. Source: HR source.
2026-10-04: Product snapshot (product) . Cogs'z describes a cloud software platform for SaaS and AI businesses focused on unit-level profitability and margin improvement. Its published scope includes cost allocation, customer and product profitability, pricing and quoting, contract management, vendor spend, and AI spend visibility and control. Source: Cogs'z | The Future of Profitability - Cogs'z. https://cogsz.com
2026-09-04: Profitability platform pages expanded (product) . Cogs'z expanded its official product pages to describe customer and product profitability capabilities for SaaS and AI businesses. Source: Customer Product Profitability - Cogs'z. https://cogsz.com/customer-product-profitability
2026-09-01: Platform modules clarified (product) . Cogs'z clarified the platform structure on its how it works page. Source: How Cogs'z works. https://cogsz.com/how-it-works
2026-05-01: Company post invites demos (gtm) . Cogs'z posted about its profitability platform on LinkedIn and invited viewers to book a demo. Source: Cogs'z post on SaaS profitability. https://www.linkedin.com/posts/cogsz_saas-profitability-financeleadership-activity-7384977331494211584-l6rU

Cost Optimization & Routing

Software that reduces AI costs by changing how work is executed. It selects cheaper execution paths when they can deliver an acceptable result.

FinChop

Website: finchop.io

FinChop is a private beta platform that reduces AI spend by routing each task to the lowest cost model that can still meet quality needs and by showing ROI across workflows.

Category: Cost Optimization & Routing. Country: Unknown. Employees: unknown.

Landscape fit: It fits this category because it changes how AI work is executed to lower cost, mainly by routing requests to cheaper models when acceptable results are likely.

Company timeline

2026-10-04: HR snapshot (hr) . The supplied homepage evidence provides no direct hiring or team signal. Source: FinChop homepage. https://finchop.io
2026-10-04: Product snapshot (product) . The supplied homepage evidence describes enterprise AI workflow ROI visibility and cost-oriented model routing, including cloud and self-hosted models. Source: FinChop homepage. https://finchop.io

Tokenistt

Website: tokenistt.com

Tokenistt is an AI FinOps platform that helps enterprises track, govern, and reduce LLM spend by routing requests across providers and optimizing execution paths.

Category: Cost Optimization & Routing. Funding stage: Pre Seed. Country: India. Employees: 5-person founding team.

Landscape fit: It fits cost optimization and routing because the product explicitly chooses cheaper model and provider paths, caches or reroutes requests, and reduces AI spend when a lower cost path can meet the quality bar.

Company timeline

2026-10-04: HR snapshot (hr) . The supplied careers-page summary describes Tokenistt as a small, remote-first, pre-seed team, with five people on the founding team and two open roles. This is current-state evidence rather than a dated hiring event. Source: Tokenistt careers page. https://tokenistt.com/careers
2026-10-04: Product snapshot (product) . Tokenistt describes an AI FinOps control plane for enterprise LLM spend. Official machine-readable company materials list monitoring, cost management, governance, routing, optimization, cache intelligence, and developer-tool integrations. Source: Tokenistt homepage. https://tokenistt.com
2026-07-01: YC application announced (gtm) . Tokenistt said it had applied to Y Combinator Summer 2026. Source: Tokenistt company post. https://www.linkedin.com/posts/tokenistt_weve-been-a-little-quiet-over-the-last-few-activity-7459357857356963840-ch6b
2026-07-01: Early workflow rollout and waitlist interest (gtm) . Tokenistt said it was rolling the product into early workflows and reported more than 300 developers on its waitlist in under 24 hours. The post also said teams were reaching out inbound. Source: Tokenistt early traction post. https://www.linkedin.com/posts/tokenistt_tokenistt-ai-finops-platform-for-enterprise-activity-7455111394712129536-3nuq
2026-07-01: Execution layer build update (product) . Tokenistt said it was building an MCP based execution layer and improving real time cost estimation before prompts are sent. It also said it had started testing cache return on investment. Source: Tokenistt build update. https://www.linkedin.com/posts/tokenistt_starting-the-week-with-a-quick-build-update-activity-7456897984006602753-UA4Z