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An AI IT company

Your AI IT company.On your cloud.

A CTO, engineers and an ops team, made of AI. They plan, build, ship and run your software on your cloud. You set how far they can go.

Join the waitlistSee how it works
AI Architect & CTO
AI Software Engineer
DevOps + SRE

Meet your newIT department.

  1. 01 / 03

    AI Architect & CTO

    Thinks like a CTO.

    Learns your business, says what to build and what not to, and directs the rest of the team.

  2. 02 / 03

    AI Software Engineer

    Builds like a team.

    Turns approved work into tested, reviewed code - delivered as pull requests you can read.

  3. 03 / 03

    DevOps + SRE

    Never goes off call.

    Ships every release and keeps your platform healthy, around the clock - by the book.

You say what the business needs. The architect decides what to build. The engineer builds it. DevOps ships and runs it. You make two decisions - and keep every key.

By the numbers

Small numbers.Big difference.

A team of

3

AI agents

A CTO, an engineer and DevOps + SRE, working as one.

Autonomy in

6

levels

From observe-only to fully autonomous. You set each one.

On call

24/7

operations

Your platform watched day and night.

Only

2

decisions are yours

Approve the plan. Approve go‑live.

Who does what

The architect leads.The team delivers. You decide.

You

The owner

  • Set goals and limits
  • Approve budgets and go-lives

AI Architect & CTO

The head of IT

  • Understands your business
  • Checks what is feasible - and what is not
  • Picks the right tech for each stage
  • Directs the engineer and DevOps + SRE
  • Brings budgets to you for approval
  • Makes the call in an emergency - and explains why

AI Software Engineer

Builds it

  • Features, fixes and integrations
  • Tests and reviews on every change
  • Docs and pull requests

DevOps + SRE

Runs it on your platform

  • Releases, monitoring and on-call
  • Scaling, backups and security
  • Best practice by default

A new request

  1. 1You say what the business needs.
  2. 2The architect works out what to build, and with what.
  3. 3It directs the engineer to build and DevOps + SRE to prepare the platform.
  4. 4Finished code goes from the engineer to DevOps + SRE for release.

One request, end to end

Eleven steps.Two decisions are yours.

“We want online ordering with loyalty points before the summer season.”
A restaurant chain owner, before the summer season
Step
01 / 11
Owner approvals
0 / 2
  1. 1

    AI Architect & CTO

    Asks the questions a good CTO would: volumes, stores, systems, deadline, budget.

  2. 2

    AI Architect & CTO

    Reviews what you already run, with the access you grant.

  3. 3

    AI Architect & CTO

    Works out what exists, what is missing and what can be reused.

  4. 4

    AI Architect & CTO

    Tells you what fits the deadline - and what does not.

  5. 5

    AI Architect & CTO

    Hands you a one-page plan: cost, timeline and risks.

    You approve the plan and budget

  6. 6

    AI Architect & CTO

    Turns the plan into work for the engineer and DevOps agents.

  7. 7

    DevOps + SRE

    Sets up development, staging and production environments.

  8. 8

    AI Software Engineer

    Builds the ordering app, loyalty and POS sync - tested and documented.

  9. 9

    DevOps + SRE

    Ships to staging, runs the launch checklist, schedules go-live.

    You approve go-live

  10. 10

    DevOps + SRE

    Keeps it healthy, handles incidents and scales for weekend peaks.

  11. 11

    AI Architect & CTO

    Reports back monthly: cost, uptime, usage and what to do next.

The right tech at the right time

Built for today.Ready for what comes next.

Most teams over-build too early or patch too late. The architect picks what fits your stage - and changes it only when the business needs it to.

Prove it works - fast and cheap.

  • Architect decides

    A simple web app and a managed database. One environment. No over-engineering.

  • Engineer builds

    Builds a working prototype you can click through.

  • DevOps + SRE runs

    One-click deploys and basic monitoring.

Decisions you can follow

It makes the call.Then it tells you why.

If something breaks at 2 a.m. and nobody can be reached, the architect takes only the smallest step that can be undone. Then it explains the decision in plain words - so you are never left guessing.

Emergency decision · checkout

From your AI Architect & CTO · 02:14 AM

Resolved
What happened
Checkout errors jumped to 18% four minutes after release v2.4. DevOps + SRE raised it.
What I did
Rolled back to v2.3 - a step your settings allow without approval. Errors are back under 0.5%.
Why I didn't wait
You and your admin didn't answer for 10 minutes. Waiting another 30 would have hit around 2,000 orders. A rollback is fully reversible.
What happens next
The engineer has found the bug and opened a fix. It needs your approval before it goes back to production.
Keep it UndoAsk a question

Illustrative example

DevOps + SRE

Your platform, run by the book.Every day. Every night.

The practices strong ops teams follow - applied to your platform from day one, not after the first outage.

  • 01

    Everything as code

    Infrastructure and config are versioned, reviewed and repeatable - no hand-made servers.

  • 02

    Safe releases

    Automated checks before every release, gradual rollout, instant rollback.

  • 03

    Watched around the clock

    Monitoring and alerts on what your customers feel, not just what servers report.

  • 04

    Incidents, handled

    Contain first, fix the cause, then write it up so it does not happen twice.

  • 05

    Backups you have tested

    Regular backups and recovery drills - because an untested backup is a hope.

  • 06

    Patched and locked down

    Updates, secret rotation and access reviews on a schedule.

  • 07

    Cost under control

    Idle and oversized resources found and fixed every month.

  • 08

    Clear service targets

    Agreed uptime and speed goals, tracked and reported to you.

Meet DevOps + SRE

Trust & control

Agents act.You decide how far.

Set an autonomy level for every kind of decision, per environment and budget. Prompts never grant permission - only a human can raise a level.

L2

Act with approval

Go ahead once the right person says yes.

For example

Release a new version to production.

  • Scoped by environmentDev, staging and production each get their own level.
  • Scoped by money and timePer-action and monthly caps; business hours or always.
  • Irreversible waits for youDeleting data, IAM changes and contracts always need a named human.

The platform underneath

Built once.Every agent runs on it.

Shared agent runtime

Coming soon

Every agent shares one engine, so every improvement reaches all of them at once - and new agents arrive fast.

  • Long jobs, no restarts

    Big work keeps going - and can wait for your approval - without starting over.

  • Remembers your project

    Your stack, decisions and history, recalled when they matter.

  • Right model for the job

    Each task goes to the model best suited to it. Quality up, cost predictable.

  • Plugs into your tools

    Your cloud and your tools, connected - and open to your own agents too.

Explore the runtime

Governance & control plane

Coming soon

An agent that can change production is a privileged user. We treat it exactly like one.

  • Only the access a task needs
  • Every action checked against your rules
  • Agent code runs in isolation
  • A complete, exportable record
  • Spend limits agents cannot cross
  • Instant kill switch
See the controls

Built for the stack you already run

Your repos. Your tools.Your cloud.

  • GitHub
  • GitLab
  • Bitbucket
  • Jira
  • Linear
  • Figma
  • Notion
  • WhatsApp
  • Sentry
  • PagerDuty
  • Grafana
  • Stripe
  • Razorpay
  • Shopify
  • Kubernetes
  • Docker
  • Terraform
  • Google Cloud
  • Cloudflare
  • PostgreSQL
  • MongoDB
  • Redis
  • React
  • Next.js
  • Node.js
  • Go
  • Python
Trademarks belong to their owners. Shown to illustrate the tools DataDack is designed to work with.

The lineup

Everything we are building.One team, one platform.

Everything here is coming soon unless marked
AI IT team

AI Architect & CTO

The head of your IT

Understands your business, tells you what to build and what not to, designs it end to end and leads the other agents.

  • CTO
  • Business analyst
  • Product strategist
  • Solution architect
  • Data architect
  • Cloud & network architect
  • +3 more
AI IT team

AI Software Engineer

Your whole delivery team

Turns approved work into tested, reviewed, documented code - pull requests your team can read, and prototypes from a prompt.

AI IT team

DevOps + SRE

Runs your platform, day and night

Runs your pipelines, infrastructure, releases, monitoring and incidents around the clock - and calls a person when it should.

Platform

Governance & Control Plane

Your rules, enforced

Decide how far every agent may go, approve what matters from anywhere, and see a full record of everything they did.

Platform

Shared Agent Runtime

One engine, every agent

The engine under every DataDack agent - memory, safe execution and continuous testing - so every agent gets better together.

Sales Automation

AI Calling Agent

Sales conversations, handled

An AI voice agent for inbound and outbound sales calls, with clear handoffs to your team and a record you can review.

Marketing Automation

Future

On the roadmap: agents that plan, run and measure your marketing - with the same controls as everything else.

See the plan

Getting started

Three steps.No hiring round.

  1. Tell it what you need

    In plain words, the way you would brief a CTO. The architect asks the questions a good one would.

  2. Set how far it may go

    Pick an autonomy level per decision and environment. Approve the plan and budget when it asks.

  3. Watch it ship and run

    Pull requests, releases and incidents arrive as reviewable artifacts - with a monthly report on all of it.

Questions

Asked.And answered.

What is DataDack?

DataDack is an AI IT company that runs on your cloud. You say what the business needs. An AI CTO decides what to build, an AI engineer builds it, and an AI ops team ships it and keeps it running. They only go as far as you allow. The main website is datadack.com.

What is datadack.si?

datadack.si is a second website for the same company, written in shorter sentences so the idea is easy to see. It is not a company in Slovenia. DataDack is based in Chandigarh, India. The main website is datadack.com, and the cloud is at datadack.cloud.

When can I use it?

The AI IT agents, governance platform and AI Calling Agent for Sales Automation are coming soon. Marketing Automation is a separate part of the roadmap and is planned for later. Join the waitlist and we will contact you when early access opens.

What is Sales Automation?

Sales Automation starts with the AI Calling Agent: it can handle approved inbound and outbound calls, hand a conversation to a person when needed, and keep a record your team can review. It is planned as a separate segment from the AI IT team.

Is Marketing Automation available?

Marketing Automation is on the roadmap for a later stage, after the core AI IT and Sales Automation products. Join the waitlist to hear when plans develop.

Hire your AI IT company.Before your next hire.

Early access opens to a small group first. Tell us what you would hand over, and we will be in touch.

Join the waitlistHow it works