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.
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.
- 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
Managed resources
prod-api · AWS us-east-1 · last synced 14:03
| Resource | Type | Status | Cost/mo |
|---|---|---|---|
| api-cluster | EKS cluster | In sync | $146 |
| api-db | RDS PostgreSQL | In sync | $58 |
| api-sg | Security group | Drifted | $0 |
| api-logs | S3 bucket | In sync | $3 |
Drift on api-sg
ingress:
443/tcp from 10.0.0.0/16 (desired)
+ 22/tcp from 0.0.0.0/0 (not in ledger)
Blast radius: api-sg only. Waits for your confirmation before anything runs.
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 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.
- 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 exactly what changed, and offers to converge back.
- 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.
Add a read replica to the API database.
Planned against your ledger
api-db is an RDS PostgreSQL instance in us-east-1, created three weeks ago in run
#142. A read replica goes in the same subnet group and security group.
- create api-db-replica-1 · db.t4g.medium · same VPC
- estimate +$58/mo · within the $500/mo project cap
- blast radius api-db reads only · no downtime
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.
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.
01
Ask in plain language
Request a one-time task, recurring workflow, or monitored operational job in the same interface.
02
Stay inside approved access
The system uses only the providers, credentials, tools, and permissions available to that user and project.
03
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
You grant OrchestrAI a role in your account. Before every run it mints a short-lived token through OIDC federation, AWS STS, Azure federated credentials, and GCP workload identity, and discards it when the run ends. Nothing you paste into OrchestrAI can act on your cloud on its own.
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.
Want to see what happens before you pay? Walk through a first run.
What a credit buys
One credit is 1,000 tokens of model work at the base rate.
Every run is metered in tokens, and the model you pick sets the rate. Claude Sonnet 5 is the default at 1x. Smaller models such as Claude Haiku 4.5 and GPT-5 mini run at 0.25x–0.5x; Claude Opus 4.8 runs at 3x. You choose the model per conversation and the multiplier is shown next to it.
Credits never expire and roll over month to month. Top-ups start at $5 at your tier's per-credit price, and unused credits are refundable in your first 14 days.
Worked example: a run that uses 40,000 tokens at 1x costs 40 credits — $0.60 on Pay As You Go, $0.48 on Pro, $0.32 on Business, $0.20 on Enterprise.
| Tier | Per credit | $5 buys |
|---|---|---|
| Pay As You Go | $0.015 | 333 credits |
| Pro | $0.012 | 416 credits |
| Business | $0.008 | 625 credits |
| Enterprise | $0.005 | 1,000 credits |
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
Most popular
Pro
$29 / month
For individual developers and power users with regular operational workloads.
- 1,500 credits included per month
- 20% credit discount on top-ups
- Email support
- Unlimited projects
Business
$199 / month
For teams and growing organizations that run operations at scale.
- 10,000 credits included per month
- 47% credit discount on top-ups
- Priority email support
- Unlimited team members
Enterprise
$2,499 / month
For large organizations. SSO, SLA, and dedicated support included standard.
- 150,000 credits included per month
- 67% credit discount on top-ups
- Dedicated account manager
- SLA and uptime guarantee
What changes at each tier
| Feature | Pay As You Go | Pro | Business | Enterprise |
|---|---|---|---|---|
| Monthly price | Pay As You Go$0 — pay as you go | Pro$29 | Business$199 | Enterprise$2,499 |
| Credits included each month | Pay As You GoNone — buy what you use | Pro1,500 | Business10,000 | Enterprise150,000 |
| Price per top-up credit | Pay As You Go$0.015 | Pro$0.012 | Business$0.008 | Enterprise$0.005 |
| Top-up discount | Pay As You Go— | Pro20% | Business47% | Enterprise67% |
| Team | Pay As You GoSingle user | ProSingle user, unlimited projects | BusinessUnlimited team members | EnterpriseUnlimited team members |
| Support | Pay As You GoCommunity | ProEmail | BusinessPriority email | EnterpriseDedicated account manager |
| SSO | Pay As You Go— | Pro— | Business— | EnterpriseIncluded |
| SLA and uptime guarantee | Pay As You Go— | Pro— | Business— | EnterpriseIncluded |
| Refund window | Pay As You GoUnused credits, first 14 days | ProUnused credits, first 14 days | BusinessUnused credits, first 14 days | EnterpriseUnused credits, first 14 days |
Get started
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.