Kritama

Kritama

Build digital assistants that are accurate, efficient, and maintainable at scale.

Product walkthrough

See Kritama in motion

A closer look at how Kritama structures context, keeps model behavior observable, and turns reusable intelligence into production assistants.

Context
Switching without noise
Signals
Runs you can inspect
Control
Policies in code

Fractal Context Engine

The Intelligence layer you can control

Dynamic Context Switching

Relevant context moves in and out as the task changes, keeping the model focused on the problem at hand without carrying unnecessary noise.

Observable Intelligence

See where problems occur, reproduce them and fix problems systematically.

N-01 ACTIVE
N-03 ACTIVE
N-08 ACTIVE
N-14 ACTIVE
N-16 ACTIVE

Small Model Advantage

Using smaller models means cheaper costs and higher throughput. Your agents respond faster and use fewer tokens.

$1.50

Cost

M output tokens

200

Throughput

tok / sec

1 - 2s

Latency

llm call

Programmable Intelligence

HCL defines the structure, markdown defines the intelligence. Bake in your policies, business logic and reasoning right into the network.

module "memovee" {
  source  = "upmaru/base/tama//modules/messaging"
  version = "0.5.6"

  depends_on = [module.global.schemas]

  name = "Memovee"
}

resource "tama_prompt" "memovee" {
  space_id = module.memovee.space_id

  name    = "Memovee Personality"
  role    = "system"
  content = file("memovee/persona.md")
}

resource "tama_space_bridge" "memovee-basic" {
  space_id        = module.memovee.space_id
  target_space_id = tama_space.basic-conversation.id
}

resource "tama_space_bridge" "memovee-media" {
  space_id        = module.memovee.space_id
  target_space_id = tama_space.media-conversation.id
}

resource "tama_space_bridge" "memovee-ui" {
  space_id        = module.memovee.space_id
  target_space_id = tama_space.ui.id
}

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