Step 01
Teams connect.
Every employee gets the assistant app: your brand, on their phone and in their browser. Tasks, messages, actions, approvals: one inbox where work actually arrives.
Kareenos: the engine for agentic business applications
An engine that sees, knows where, and speaks every channel.
Vision, GPS, voice, messaging, your database, any API: every signal becomes a typed event. AI agents reason, code jobs execute, and the results land where work happens: tasks, messages, your employees' assistant app, and the systems you already run. And your clients build all of it themselves, in plain language.
Not a chatbot.Not a copilot.Not another workflow builder.A fully autonomous agentic engine.
- Built by your clients
- Event-driven
- Multi-tenant
- On-premises
For software companies, agencies & platforms
You have clients. Give every one of them an operations engine, under your brand.
One engine runs all your clients, each fully isolated. Build a capability once. Every client gets it. Fix it once. Every client inherits the fix. And your clients extend it themselves, in plain language, without a ticket to you. Onboard the next client by configuring, not rebuilding.
- One engine, all your clients, each in their own isolated space
- Author once, deploy to everyone. Updates and fixes included
- Your clients build their own agents: no ticket, no sprint, no roadmap
- Your brand, your infrastructure, your customer relationship
- Docker images, live in 30 minutes
- Built by your clients
- Event-driven
- Multi-tenant
- On-premises
What runs under your brand
Agents and their teams. One loop. Operations that never sleep.
This is what your clients get: agents that assist, track, and support their teams, with tasks, calls, messages, and follow-ups handled end to end. Every employee gets an assistant app. Every system stays connected. Nothing waits, nothing slips, and nobody chases.
Not a chatbot.Not a copilot.Not another workflow builder.An agentic engine that runs operations.
- Built by your clients
- Event-driven
- Multi-tenant
- On-premises
hub Event Bus typed events
smart_toy AI Agent
precision_manufacturing Code Job
grid_on Live Sheet
photo_camera Vision
task_alt Tasks
my_location GPS
forward_to_inbox Messages
graphic_eq Voice
smartphone Assistant App
chat Messaging
sync_alt Third-party APIs
How it runs
From signal to done.
Without a human dispatcher.
Step 02
Agents run the loop.
They assign tasks, track progress, chase what's late, and escalate what matters. Around the clock, across every client.
Step 03
Agents reach the systems.
Your platform, their databases, any API or MCP server. Read and write. The engine works with the data operations already live in.
Step 04
Agents work every channel.
Email, WhatsApp, Telegram, SMS, and live phone calls, inbound and outbound. One agent, every place people already talk.
01smartphoneApp
02smart_toyAgents
03apiSystems
04forumChannels
hub Event Bus typed events
Where Kareenos is different
Automation tools move data. Kareenos moves teams.
A shift gets dropped. An agent finds cover before the supervisor wakes up. An order stalls. An agent chases the supplier and updates the customer. An invoice goes unpaid. An agent calls. People do the work; agents make sure nothing waits, nothing slips, and nobody chases.
- Tasks and actions assigned to the right person, tracked to done
- Agents follow up on people, not just records, by message or by phone
- Escalations reach a human the moment judgment is needed
- The whole loop is observable: every task, call, and decision on the record
smart_toyShift Coverage Agent online · actingmore_horiz
mic0:10“Can’t make my 6 a.m. shift, sorry…”
Got it, Sara, feel better. I’m contacting 3 qualified caregivers near the client now.
task_alt Shift covered · Maria T. confirmed · 5:52 a.m.
chatOrder Chase Agent4:12 p.m.
Order stalled at the supplier. Chased on WhatsApp, customer updated with the new ETA.
check on track · customer notifiedphone_in_talkInvoice Agentday 14
Invoice two weeks overdue. Reminders sent, now on a live call with the customer.
on the phone · liveThe assistant app
Every employee gets an assistant. Under your brand, on their phone.
Tasks with proof attached: photos, scans, signatures when the job needs them. Voice notes agents understand. Live location when the work calls for it. Messages, actions, and approvals in one place, on web and mobile.
- One inbox for everything agents send: tasks, alerts, requests, reports
- Two-way: employees reply, attach, approve, or push back, and agents adapt
- Works for a warehouse, a care team, a support desk, or a fleet. Same app
- White-labeled: your logo, your colors, your domain
support_agentYourBrand Assistant onlinenotifications
task_altNew task · Visit #4187due 2 pm
Confirm the install and attach a photo when done.
photo_camera photo proof requiredhow_to_regApproval requested
Reorder 40 units for site B?
check Approveclose Push backpersonYou · reply0:12
“On it, photo coming right after the install.”
smart_toyOps Agentnow
Thanks, photo received. Tomorrow's route is on your board.
my_locationLive location · Visit #4187on route
The part nobody else ships
Your clients build it. Not your engineers.
The builder agent interviews the client, plans, and assembles agents, code jobs, live sheets, and screens, so your clients add capabilities to your platform without a ticket, a sprint, or a limit. Your roadmap stops being the bottleneck.
- Plain language in, running system out
- Interview → plan → assemble, with approval gates
- Every client builds inside their own isolated space
- What they build runs on all the machinery below
smart_toyBuilder Agent online · actingmore_horiz
I need to chase unpaid invoices and call the ones who don't reply.
I'll assemble that: an agent watching your invoices sheet, a nightly job that flags overdue ones, and live calling for non-responders.
task_alt Live · agent + job + sheet · built in minutes
One request, end to end
From a client's sentence
to a running system.
A client asks in plain language. The builder assembles the pieces. Signals flow in, the engine reasons and executes, and the results land where work happens.
photo_cameraVision
my_locationGPS Location
graphic_eqVoice
chatMessaging
storageDatabase
apiAPIs
hubEvent Bustyped events · isolated per client
smart_toyAI Agent
precision_manufacturingCode Job
grid_onLive Sheet
task_altTasks & Actions
forward_to_inboxMessages & Email
smartphoneAssistant App
sync_altThird-party Systems
Connected on day one
What the engine perceives
Operations happen in photos, places,
and conversations. The engine reads all three.
Vision
Photo sessions become detections agents judge.
A capture session uploads photos plus an optional voice note into a named camera channel. The note is auto-transcribed, the session fires its event, and every subscriber wakes: code jobs run detection models over the photos, AI agents judge the detections together with the transcript.
- Capture from mobile or web into named camera channels
- YOLO26 object detection and InsightFace embeddings in the Python tier
- Voice notes auto-transcribed and attached to the session
- Multiple subscribers share one session record: detections, transcript, verdicts
photo_cameraDock Cameracapture session · 3 photos + voice notesession 4c1a
mic voice note → “third bay, check the damaged crate”
session ready → 2 subscribers woke · YOLO26 + judging agent
Location
Geofences, live tracking, and routes as events.
Any object can be tracked live: a user, a vehicle, a sheet row. Zones drawn as points, lines, or polygons fire edge-triggered check-in and check-out events with dwell logic, and durable geofence subscriptions wake the agents and jobs you bind to them.
- Live map plus historical playback for every tracked object
- Geocoding, reverse geocoding, and driving routes up to 23 waypoints
- OR-Tools route optimization: about 1–2s for 30 stops
- Geofence events wake agents and jobs the moment they happen
my_locationFleet Watch Agentvan 14 · re-routed around delayETA 11:42
bolt zone entered → check-in task created · route re-optimized in 1.2s
Channels
One agent, every place people already talk.
The same agent answers a WhatsApp voice note, picks up a live phone call, speaks in the browser over WebRTC, drives an approved browser tab, and assigns tasks to a phone in the field. Transport is a channel; the agent is the brain.
- WhatsApp, Telegram, SMS, and email: two-way, with media
- Live phone calls: answer, initiate, barge-in, transfer to a human or another agent mid-call
- In-app voice over WebRTC with a real-time transcript
- Attended browser automation in the user’s own signed-in session, behind approval gates
smart_toySupport Agent online · actingmore_horiz
mic0:10“Where's my order? The crew's already on site…”
Order #2231 left the warehouse at 8:10. The driver is 20 minutes out. I'll message you the moment it arrives.
task_alt Answered on WhatsApp · #2231 · out for delivery
The agentic framework
One event bus. Seven building blocks.
This is how agentic business applications are assembled on Kareenos. Every block below links to its full spec and its Kareenos name on the platform page.
the builder
The Builder Agent
Your clients describe what they need in plain language. It interviews, plans, then assembles the agents, jobs, and sheets in dependency order, with approval gates.
Learn more arrow_forwardthe workforce
AI Agents
Versioned reasoning units subscribed to events. Tool-permissioned, so zero grants means zero tools. Session and long-term memory built in.
Learn more arrow_forwarddeterministic muscle
Code Jobs
Sandboxed JavaScript with five trigger types, plus a Python tier for real compute. No model in the loop; cost and latency stay predictable.
Learn more arrow_forwardthe knowledge
Documents
Agent-authored reports, SOPs, and evidence, with bilingual full-text search and revocable public share links.
Learn more arrow_forwardthe data substrate
Live Sheets
Real-time collaborative sheets with formula, lookup, and geometry columns. Every row change fires an event downstream code can react to.
Learn more arrow_forwardyour database, live
Data Connectors
Read-only connectors expose Postgres, MySQL, MSSQL, Cassandra, Mongo, REST, and GraphQL sources as live sheets. Writes are rejected by construction.
Learn more arrow_forwardyour systems, agent-callable
Custom Tools
Author tools against your own databases and services, and grant them to agents like any built-in. Each call is identity-mapped to the acting account.
Learn more arrow_forwardTwo tiers of execution
Code when you want it. Agents when you don't.
Deterministic work runs as sandboxed JavaScript that reads sheets, fires events, and calls agents, with a Python tier for real compute: OR-Tools, numpy, pandas, scipy, networkx, torch. No model in the loop, so cost and latency stay predictable. The model is used only where judgment is needed.
- Code jobs read and write sheets, fire events, and call agents
- Python for compute: optimization, statistics, detection models
- Explicit per-job grants: sheets, events, agents, location, camera
- Budget caps per run: reasoning, compute, and vision all metered
event
payment_overdue
AI Agent · reasons
tone: second reminder → schedule a call
Code Job · executes
Agents reason. Jobs execute.
Flows people run on Kareenos
Trigger in. Reasoning and code. Result out.
Six real flows, exactly as they run. Each chip is a component from the framework above.
edit_note client · plain-language request
The builder agent interviews, plans, then assembles an agent, a code job, and a live sheet, wired and running.
A new capability ships on your platform without touching your roadmap.
- Builder Agent
- AI Agent
- Code Job
- Live Sheet
chat whatsapp · message in
The support agent looks the order up in a live sheet and replies with delivery status. Voice note in, text out.
Customer answered in seconds; the full contact history stays queryable.
- AI Agent
- Live Sheet
- Messaging
my_location gps · location update
A detector agent checks the trip against approved zones and publishes an unauthorized-stop event; an alerter notifies the supervisor and messages the driver.
The driver’s reply is classified and a third agent closes the incident row.
- AI Agents ×4
- Event Bus
- GIS
table_chart sheet · row added
A code job reads the new delivery row and runs the OR-Tools solver in Python: 30 stops in about a second.
The route sheet updates live and the driver gets the new stop order.
- Code Job
- Python
- Live Sheet
location_on geofence · vehicle arrives
A geofence subscription wakes a code job that creates a check-in task: photo, QR scan, signature, straight to the driver’s phone.
The supervisor’s dashboard reflects the delivery the moment it’s confirmed.
- Code Job
- GIS
- Mobile
photo_camera camera · session ready
A code job runs YOLO26 over the photo batch; a judging agent reads the detections plus the transcribed voice note and classifies severity.
Incident logged automatically, with evidence, detections, and a severity call.
- Code Job
- AI Agent
- Vision
Yours to run
Docker images to running agents
in 30 minutes.
Step 01
Min 0–10
Pull the images
Docker images pulled into your VPC, on-prem cluster, or cloud account.
Step 02
Min 10–20
Connect your database
Read access to your database. The builder agent maps your schema and generates connectors.
Step 03
Min 20–25
Brand it
Logo, colors, domain. Your customers see your name, not ours.
Step 04
Min 25–30
Agents go live
First agents running. Mobile app live. WhatsApp connected.
isolation
Isolation by construction
Nested tenancy with a hard runtime boundary. Events reach only the client they belong to, never a neighbor.
permissions
Grants and approval gates
Zero tool assignments means zero tools. Jobs need explicit grants per sheet, event, and agent; sensitive work waits for human approval.
observability
Audit by event
Every tool call, job run, and row change fires an event. The platform's own activity is observable and reactable.
Your infrastructure, your brand, your customer relationship. The engine is ours to maintain, yours to run.
30 minutes to deploy · one engine per partner · every client isolated
Who builds on Kareenos
Two kinds of builders run this engine.
For software companies
You build vertical software.
Ship the complete agentic layer under your brand, beside the product you already have, on the infrastructure you already run.
- arrow_forward The full engine next to your existing product
- arrow_forward Your clients build their own agents, so features ship without your roadmap
- arrow_forward Your infrastructure, your data, your customer relationship
- arrow_forward Docker images, live in 30 minutes
For agencies & builders
You build automations for clients.
Run one engine for all your clients. Author once. Every client gets it. Fix once. Everyone inherits the fix.
- arrow_forward One engine, all your clients, each fully isolated
- arrow_forward Onboard the next client by configuring, not rebuilding
- arrow_forward Your brand in front. Your clients never see us
Either way
Want to see what their clients get?
Agents and their teams in one loop: tasks, calls, messages, and follow-ups handled end to end, under your brand.
See what runs under your brand arrow_forwardA small ask
Thirty minutes.
One demo. No deck.
We'll show you Kareenos running against a sample of your real data, in a sandbox we spin up before the call. Your market, your schema, your use case.
What you get: a working Kareenos sandbox configured for your platform, plus the technical deployment spec.