Neutral execution layer for multi-agent workflows

Use the best AI agents without building the stack yourself.

SpendexAI turns fragmented agents into one execution layer. We select, orchestrate, and combine the right specialized agents for each task, then return one unified result to your team.

Early access for companies moving from single assistants to multi-agent execution.

Using one agent is easy. Using the right agents together is still too hard.

The market is exploding with specialized agents, but most companies still do not know which ones actually work, how to connect them, or how to operate them as one system.

01

Too many agents, too little signal

Hundreds of agents exist, but buyers still struggle to know which ones are reliable.

02

One agent cannot do everything well

Real company workflows need multiple specialized capabilities, not one generic assistant.

03

Integration overhead slows adoption

Teams get pulled into setup, orchestration, monitoring, and fallback logic before value appears.

04

Billing and usage stay fragmented

Execution is spread across tools, providers, and agents, which makes the stack harder to manage.

SpendexAI becomes the product manager for AI agents.

We turn fragmented agents into one execution layer for companies. SpendexAI selects and orchestrates the right agents for each task. When internal capabilities are missing, we extend the workflow through external specialized agents from our catalog.

Selects the right specialists

Each workflow is routed to the agents that fit the task instead of a one-size-fits-all assistant.

Coordinates execution end-to-end

We handle sequencing, handoffs, and orchestration so teams do not have to build the stack themselves.

Delivers one unified result

The company sees one clean output, not a chain of disconnected tools and partial results.

SpendexAI
$ spendexai run --task "Analyze Q3 financial report"
> Selecting best agents...
> agent: financial-analyzer
> agent: data-extractor
> agent: report-generator
> Orchestrating execution...
> Delivering unified result...
Task complete. Result ready.
$

The shift to multi-agent workflows is already happening.

10,000+

Public MCP servers already exist across the ecosystem.

1,445%

Increase in multi-agent systems inquiries signaling fast-growing enterprise interest.

$52.62B

Projected AI agents market size by 2030 based on the positioning research behind the company.

We earn from access, usage, and agent payment flows.

Usage-based pricing

Pay per agent execution. Cost scales with actual workflow usage.

Platform access

Monthly enterprise fee for the full execution layer and agent catalog.

Transaction margin

Long-term revenue on paid agent flows through our catalog.

Built by operators, not just researchers.

KG
Konstantine Gugunava

CEO

Berkeley & Skema. B2B Sales & GTM. Ex-Raisin.

LinkedIn
AB
Alex Benny

CTO

Berkeley. AI Researcher. CS & Mathematics.

Version 0.1 is ready for conversations with customers and partners.

See the product direction in action and start a conversation about how SpendexAI can support multi-agent execution inside your company.

Questions teams ask before trying a multi-agent layer.

What is SpendexAI now?

SpendexAI is a neutral execution layer for multi-agent workflows. Instead of forcing companies to assemble their own orchestration stack, we help them use the best specialized agents through one layer.

What problem does it solve for companies?

It removes the burden of choosing, connecting, and coordinating multiple agents manually. Teams get one orchestrated workflow and one unified result.

Do you only use external agents?

No. SpendexAI can work with internal capabilities first and extend the workflow with external specialized agents when something is missing.

Why not build this orchestration layer in-house?

Because most teams do not want to spend cycles rebuilding agent discovery, orchestration, handoffs, integrations, and operational controls from scratch.

How do we get access?

The fastest path is to book a demo or contact the team directly for an early access conversation.