The AI cloud engineer

The AI engineer that runs your cloud — and remembers everything it built.

Deploy, maintain, monitor, and secure AWS, GCP, Azure, and the tools around them in plain language. Every resource OrchestrAI creates lands in a desired-state ledger, so it can spot drift, explain what changed, and converge back — and every mutation waits for your explicit confirmation before it runs.

Connect your cloud See pricing

A ledger of everything it built: desired state without Terraform files
Confirm gates, spend caps, and short-lived credentials on every action
One chat across cloud, data, networking, cost, and security — ~1,000 tools

Example prompts

Cloud delivery, maintenance, networking, cost, and security work flowing through one system.

50+ prompts in motion

Access model

Admin + user scoped

Run modes

One-time, scheduled, monitored

Visibility

Progress, logs, artifacts, replay

Built for the stack startups already run

A control layer across cloud platforms and the tools around them.

AWS GCP Azure Snowflake Terraform Kubernetes dbt GitHub GitLab PagerDuty

Two modes

On its own, or alongside the tools you already use.

The ledger

It remembers what it built. Then it defends it.

Every resource OrchestrAI creates is recorded in a managed-resource ledger: what it is, how it's configured, and why it exists. That memory is what separates an AI engineer from a chatbot with CLI access.

Desired state

Desired state without Terraform

No HCL, no state file, no plan/apply ceremony. Describe the outcome and the ledger becomes your source of truth — and you can export to Terraform anytime.

Drift detection

Someone touched prod? It notices.

When a security group is edited by hand or a config quietly changes, OrchestrAI surfaces the drift against desired state, shows you exactly what changed, and offers to converge back.

Cross-session memory

Context that survives the chat

Three weeks later, it still knows what it deployed, how services connect, and what your budgets are. Every new request is planned against the infrastructure you actually have.

Startups

More operational coverage from the team you already have.

OrchestrAI is aimed at companies that need serious cloud, data, and security execution before they can justify a large platform or enterprise operations team.

Development speed

Ship infrastructure and platform work faster

Collapse backlog work like environments, deployments, pipelines, and operational setup into natural-language requests instead of manual handoffs and console work.

Operational cost

Reduce spend before waste becomes normal

Estimate cost before changes go live, monitor spend as work runs, and turn optimization reviews into ongoing operational hygiene.

Small teams

Give lean teams broader coverage

Let one or two people cover infrastructure, networking, data operations, and security-driven maintenance without living in tickets and brittle runbooks.

Performance

Catch and correct issues earlier

Use the system to monitor health, investigate regressions, scale ahead of demand, and keep environments performing well as usage grows.

Security

Move fast without opening up the stack

Keep execution bound to project access, approved credentials, role controls, approvals, and auditable run history while also helping teams tighten cloud security posture.

Teams

Give everyone the power to ship infra — inside guardrails you set.

Team controls aren't roadmap. Role-based access, org and project scoping, approval routing, and a full audit trail are live today, so you can open infrastructure up to the whole team without opening up production.

Access control

RBAC with org and project scoping

Admins decide who can run what, where, and with which credentials. Every user and project operates inside explicitly granted boundaries — nothing more.

Approval routing

An approval inbox for risky work

Sensitive or expensive changes route to the right approvers before anything runs. Requests carry the plan, the cost estimate, and the blast radius.

Audit and replay

Every run recorded and replayable

What ran, who approved it, what changed — durable run history and replay give you the receipts for incident reviews, security questions, and compliance asks.

How it works

You describe the outcome. OrchestrAI handles the routing.

Ask in plain language

Request a one-time task, recurring workflow, or monitored operational job in the same interface.

Stay inside approved access

The system uses only the providers, credentials, tools, and permissions available to that user and project.

Follow work live

Track progress, logs, health signals, outputs, and what changed while the work runs, then review the run later if needed.

Built for startup teams running AWS, GCP, Azure, ML/AI, CI/CD, and on-call workflows with growing operational load and limited headcount.

Coverage

From shipping product to keeping the platform healthy.

The product surface already spans cloud delivery, maintenance, networking, security, cost, data engineering, and connected operational tooling.

Cloud delivery

Environments, clusters, storage, and databases

Kubernetes clusters, compute, storage, databases, SSL, and load balancing
Safer rollout work for production, staging, and development environments
Reusable setup for the cloud foundations startups need early

Maintenance and reliability

Monitoring, failures, incidents, and recovery

Summaries of failed jobs, unhealthy services, queue pressure, and noisy systems
Scheduled maintenance, recurring checks, and monitored operational workflows
Replayable history to understand what happened and what changed

Networking and secops

Cloud networking and security posture work

VPCs, subnets, routing, security groups, network policies, and access reviews
Public exposure checks, IAM reviews, audit trails, and compliance-oriented reporting
Operational investigation of traffic spikes, risky changes, and security drift

Cost and performance

Budget awareness and system efficiency

Cost estimates before execution and ongoing monitoring once workloads run
Right-sizing, savings opportunities, and budget-aware recommendations
Performance tuning for latency, scaling, capacity, and throughput

Data and AI workflows

Pipelines, warehouses, quality checks, and ML ops

ELT and pipeline work across PostgreSQL, S3, Snowflake, BigQuery, dbt, and more
Backfills, quality checks, monitoring, model workflows, and scheduled runs
Natural-language coordination across data preparation, training, and deployment

Connected services

Work that spans the tools around the cloud

GitHub and GitLab for release context and pipeline-triggered follow-up work
Snowflake and warehouse context before planning or execution
PagerDuty and operational notifications when monitored flows need escalation

Security and control

An AI with production access should have to ask permission. Ours does.

Every mutation goes through the same safety perimeter: propose, show the plan and cost, wait for your confirmation, execute inside scoped access, and record the run.

Propose → confirm on every mutation

Nothing changes until you approve the plan. Destructive operations go further and require a typed risk phrase, so a stray "yes" can never tear down production.

Short-lived credentials, never stored keys

Cloud access uses OIDC federation — AWS STS, Azure, and GCP workload identity — to mint temporary tokens per run. Connection secrets are envelope-encrypted at rest.

Spend caps and sandbox mode

Cost estimates before execution, per-project spend limits enforced at run time, and a sandbox mode for rehearsing changes without touching real infrastructure.

Full audit trail with replay

Live progress, logs, and artifacts for every run, plus durable, replayable history for security review, compliance, and incident forensics.

Where it fits

App builders, coding agents, and OrchestrAI.

Three different jobs. Here is how they compare, row by row — including the rows where the tools you already use do the same thing we do.

Pricing

$5 to start. Refundable in your first 14 days.

Pay As You Go starts with a $5 minimum credit purchase. If it's not for you, request a refund within your first 14 days and we'll return whatever you didn't use. Credits never expire and roll over each month. Upgrade when you need more capacity and team features.

Pay As You Go

$5 minimum, pay as you go

No subscription. Buy credits as needed for occasional operations work — unused credits are refundable in your first 14 days.

Natural-language operations
AWS, GCP, Azure connectivity
Live run visibility and logs
Community support

Start for $5

Live now for teams that need serious operational leverage.

Sign up, connect your cloud read-only in minutes, and see your resources, drift, and cost breakdown. Approve your first execution when you're ready — nothing runs without your confirmation.

Platform Infrastructure Data Security-minded engineering