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xpander.ai

by xpander.ai

AI Agents & OrchestrationAgent DevelopmentGovernance & SecurityEnterprise Platform

Vendor-neutral enterprise AI agent platform with a universal agent harness and Omni, an AI forward-deployed engineer

Usage-based · Contact for pricing·Added Sep 17, 2026·Updated Sep 17, 2026
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THE DAILY BRIEF
xpander.ai

by xpander.ai

AI Agents & OrchestrationAgent DevelopmentGovernance & SecurityEnterprise Platform

Vendor-neutral enterprise AI agent platform with a universal agent harness and Omni, an AI forward-deployed engineer

Usage-based · Contact for pricing

xpander.ai is an enterprise AI agent platform that lets companies build, run and govern AI agents inside their own cloud or on-premises environment, across any model or framework. It is aimed at CIOs and platform teams who want employees using agents in Slack, Teams, ChatGPT or Claude without a months-long infrastructure project or vendor lock-in.

At a Glance

Category
AI Agents & Orchestration
Pricing
Usage-based, Contact for pricing
Target Market
CIOs, CTOs, Heads of AI, Platform Engineering Teams, Enterprise Developers
Deployment
Hybrid, Multi-cloud, Self-hosted
Founded
2024
Headquarters
San Francisco, United States

Key Features

  • Universal agent harness
  • Omni forward-deployed engineer
  • Identity-scoped governance
  • Credential vault
  • Deploy anywhere
  • Connectors and access protocols

Capabilities

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

Use Cases

  • Employee agent teammates
  • Sovereign or regulated deployment
  • Laptop-to-production migration
  • Engineering workflow automation
  • Model cost benchmarking

Ideal For

Best For

  • Enterprises that need agents to run inside their own VPC, on-premises or air-gapped environment
  • Platform teams standardising agent governance across multiple models and frameworks
  • Rolling agents out to employees through Slack, Microsoft Teams, ChatGPT or Claude
  • Moving prototype agents from developer laptops into governed, long-running production workloads

Not Ideal For

  • Small teams that want to try it self-serve today: there is no self-serve trial, and access starts with a booked demo and pilot setup
  • Buyers who need a long public track record: the company was founded in 2024, is seed-funded, and has almost no independent user reviews yet
  • Organisations that want flat, predictable pricing: credits are consumed per agent activation, per tool call and per model token, so scheduled or high-volume runs can grow costs quickly

Market Analysis

Enterprise-gradeVendor-neutralEarly-stage

Pros

  • Deploys inside the customer's own cloud, VPC, on-premises or air-gapped environment
  • Model- and framework-agnostic, reducing lock-in to a single AI vendor
  • Governance built in: identity-scoped permissions, audit trails, spend attribution, approval steps and a credential vault
  • SOC 2 Type II and GDPR compliance, with unlimited seats under credit pricing
  • Omni's Product Hunt launch finished #2 of the day on 17 August 2026 with 378 upvotes

Cons

  • Product Hunt commenters were skeptical about how much of Omni's 'fixes itself' automation works without a human stepping in
  • Commenters flagged token spend on scheduled runs as the usual cost trap, and credits are charged per activation, per tool call and per token
  • No self-serve trial: evaluation requires booking a demo and a pilot setup
  • Early-stage, seed-funded vendor: Omni had no Product Hunt reviews at launch, we found no G2 listing, and the 90.9% GAIA score is self-reported

Pricing

Team

Usage-based: $100 per 10,000 credits

  • Unlimited agents and workflows
  • Unlimited seats with no per-user fees
  • Hundreds of models available
  • Access from Slack, Teams, ChatGPT and Claude

Enterprise

Contact for pricing

  • Annual license starting at 50 agents
  • Self-deployment on Kubernetes or on-premises
  • SSO/OIDC
  • Private model gateway and negotiated or bring-your-own model keys
  • Sub-organisations with pooled credits
  • Dedicated support and onboarding

The Team plan is credit-based at $100 per 10,000 credits: one credit per agent activation, one per tool call, plus model tokens at published credit rates (for example 375 credits per million Claude Sonnet 5 input tokens and 1,875 per million output tokens). Seats are unlimited. Enterprise is an annual license starting at 50 agents with custom pricing, self-hosting, SSO and negotiated model rates. There is no self-serve trial; teams book a 30-minute demo to start a pilot.

Security & Compliance

soc2
gdpr
hipaa
iso27001
sso
data residency

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xpander.ai is an enterprise AI agent platform that lets companies build, run and govern AI agents inside their own cloud or on-premises environment, across any model or framework. It is aimed at CIOs and platform teams who want employees using agents in Slack, Teams, ChatGPT or Claude without a months-long infrastructure project or vendor lock-in.

xpander.ai is a San Francisco-based enterprise AI enablement platform founded in 2024 by former AWS engineers David Twizer (CEO), Moriel Pahima (CTO) and Ran Sheinberg (CPO). Its core technology is what the company calls a universal agent harness: a model-, framework- and cloud-agnostic runtime that executes AI agents as portable workloads inside a customer's own environment (AWS, Google Cloud, Azure, a private VPC, on-premises or air-gapped) while rendering agent interfaces securely on demand. The harness supports coding-agent runtimes such as Claude Code, Codex and OpenCode, its MIT-licensed open-source SDK works with frameworks including Agno, LangChain, PydanticAI and CrewAI, and it can call models from providers such as OpenAI, Google Gemini, Meta Llama, Qwen, DeepSeek and Mistral. On top of the runtime sits Omni, launched on Product Hunt on 17 August 2026 and described as an agentic forward-deployed engineer: a user describes the agent they need in plain language inside Slack, Microsoft Teams, ChatGPT or Claude, and Omni sets it up, troubleshoots failed runs and benchmarks models for cost at equal quality. The company reports a 90.9% score for Omni on the GAIA agent benchmark, a vendor-reported figure. Governance features include per-user agent permissions tied to identity, full audit trails with spend attribution, a credential vault that keeps secrets away from models, human approval steps inside shared conversations and budget controls, and the platform is SOC 2 Type II certified and GDPR compliant. On 17 August 2026 xpander announced a $7.5 million seed round led by Pico Venture Partners with Emerge Ventures, Samsung Next and SeedIL, and says the platform is used by global enterprises in retail, manufacturing, financial services, technology and government. It positions itself against hyperscaler agent platforms as a neutral layer that avoids lock-in to any single model or cloud.

Ideal Buyer

A CIO or platform-engineering lead who must roll AI agents out to many business teams while keeping them inside the company's own cloud and under central governance.

Key Benefit

Employees get working agents in the chat tools they already use, while IT keeps per-user permissions, audit trails and spend attribution in one control plane.

At a Glance

Category
AI Agents & Orchestration
Pricing
Usage-based, Contact for pricing
Target Market
CIOs, CTOs, Heads of AI, Platform Engineering Teams, Enterprise Developers
Deployment
Hybrid, Multi-cloud, Self-hosted
Founded
2024
Headquarters
San Francisco, United States

Key Features

  • Universal agent harness

    A model-, framework- and cloud-agnostic runtime that runs agents as portable workloads inside the customer's own environment, reducing vendor lock-in.

  • Omni forward-deployed engineer

    Builds, troubleshoots and optimises agents from plain-language requests in Slack, Teams, ChatGPT or Claude, so non-engineers can adopt agents without a setup project.

  • Identity-scoped governance

    Per-user agent permissions, full audit logs with spend attribution, budget controls and human approval steps keep every agent action accountable to a named user.

  • Credential vault

    Keeps API keys and other secrets out of model context, lowering the risk that prompts or agent outputs leak credentials.

  • Deploy anywhere

    Runs on AWS, Google Cloud, Azure, private VPCs, Kubernetes, on-premises or air-gapped infrastructure to meet data-residency and sovereignty requirements.

  • Connectors and access protocols

    Agent Studio advertises 100+ connectors, and agents are reachable through REST API, webhooks, the CLI, the Python SDK and MCP.

Capabilities

text generation
image generation
video generation
code generation
workflow automation
api access
audio generation
fine tuning
agent orchestration

Use Cases

  • Employee agent teammates

    Business teams request an agent in Slack or Teams, and Omni configures it with the right permissions and connectors to company systems.

  • Sovereign or regulated deployment

    Financial-services and government organisations run agents inside a private VPC or air-gapped network so data and credentials stay inside their perimeter.

  • Laptop-to-production migration

    Engineering teams move agents prototyped locally with Claude Code, Codex or open-source frameworks into governed, long-running cloud workloads with audit trails.

  • Engineering workflow automation

    Developers build agents that act on Jira, GitHub and cloud accounts, such as reviewing pull requests or triaging tickets, behind human approval gates.

  • Model cost benchmarking

    Teams use Omni to compare models on cost at equal output quality before committing a recurring workload to a specific provider.

Ideal For

Best For

  • Enterprises that need agents to run inside their own VPC, on-premises or air-gapped environment
  • Platform teams standardising agent governance across multiple models and frameworks
  • Rolling agents out to employees through Slack, Microsoft Teams, ChatGPT or Claude
  • Moving prototype agents from developer laptops into governed, long-running production workloads

Not Ideal For

  • Small teams that want to try it self-serve today: there is no self-serve trial, and access starts with a booked demo and pilot setup
  • Buyers who need a long public track record: the company was founded in 2024, is seed-funded, and has almost no independent user reviews yet
  • Organisations that want flat, predictable pricing: credits are consumed per agent activation, per tool call and per model token, so scheduled or high-volume runs can grow costs quickly

Integrations

SDK Available
SDK:Python

Deployment

On-Premise

Market Analysis

Enterprise-gradeVendor-neutralEarly-stage

Pros

  • Deploys inside the customer's own cloud, VPC, on-premises or air-gapped environment
  • Model- and framework-agnostic, reducing lock-in to a single AI vendor
  • Governance built in: identity-scoped permissions, audit trails, spend attribution, approval steps and a credential vault
  • SOC 2 Type II and GDPR compliance, with unlimited seats under credit pricing
  • Omni's Product Hunt launch finished #2 of the day on 17 August 2026 with 378 upvotes

Cons

  • Product Hunt commenters were skeptical about how much of Omni's 'fixes itself' automation works without a human stepping in
  • Commenters flagged token spend on scheduled runs as the usual cost trap, and credits are charged per activation, per tool call and per token
  • No self-serve trial: evaluation requires booking a demo and a pilot setup
  • Early-stage, seed-funded vendor: Omni had no Product Hunt reviews at launch, we found no G2 listing, and the 90.9% GAIA score is self-reported

Pricing

Team

Usage-based: $100 per 10,000 credits

  • Unlimited agents and workflows
  • Unlimited seats with no per-user fees
  • Hundreds of models available
  • Access from Slack, Teams, ChatGPT and Claude

Enterprise

Contact for pricing

  • Annual license starting at 50 agents
  • Self-deployment on Kubernetes or on-premises
  • SSO/OIDC
  • Private model gateway and negotiated or bring-your-own model keys
  • Sub-organisations with pooled credits
  • Dedicated support and onboarding

The Team plan is credit-based at $100 per 10,000 credits: one credit per agent activation, one per tool call, plus model tokens at published credit rates (for example 375 credits per million Claude Sonnet 5 input tokens and 1,875 per million output tokens). Seats are unlimited. Enterprise is an annual license starting at 50 agents with custom pricing, self-hosting, SSO and negotiated model rates. There is no self-serve trial; teams book a 30-minute demo to start a pilot.

Security & Compliance

soc2
gdpr
hipaa
iso27001
sso
data residency

Connect

Sources

This page was written from 8 sources, 6 on domains other than xpander.ai.

  1. 1.xpander.aixpander.aivendor
  2. 2.xpander.aipricingvendor
  3. 3.docs.xpander.aidocs.xpander.ai
  4. 4.github.comxpander.ai
  5. 5.prnewswire.comxpander raises 7 5m seed to unleash ai for enterprises 30285
  6. 6.fintech.globalxpander raises 7 5m to fix enterprises ai adoption gap
  7. 7.thefastmode.com50267 xpander raises 7 5m to accelerate enterprise ai and ai
  8. 8.producthunt.comomni by xpander
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