Production AI runtime

The runtime layer
for production AI.

Jixi turns unpredictable AI into systems you can observe, control, andtrust in production.

Observable

Every execution traced: inputs, outputs, tool calls, cost, and latency in one runtime layer.

Constrained

Cost caps, token limits, and execution bounds enforced before problems reach production.

Reversible

Every workflow versioned and rollback-ready the moment behavior shifts.

Built for real use cases

Powering AI systems across industries.

Jixi powers production AI across industries where behavior, cost, and reliability matter. From real-time game systems to regulated healthcare workflows, teams use Jixi to ship faster without losing control.

Gaming

Content at scale.
Behavior under control.

Jixi powers on-demand content generation across games, from dynamic NPCs to fully generated environments. Orchestrate behavior, generate media, and keep costs and quality under control as your systems grow.

Use cases
  • AI-generated NPC dialogue, memory, and behavior
  • Dynamic storylines, quests, and world-building
  • On-demand asset generation: music, images, voice, and 3D content
  • Procedural locations and level design
Why Jixi
  • Fast, low-latency responses for responsive systems
  • Built-in cache for generated content, a GenAI CMS
  • Full control over cost, performance, and behavior at scale
SDKs
Unity logo Unreal Engine logo

Production-ready AI systems for games that evolve without breaking.

Gaming industry use case visual

In production

Built for teams running AI at scale.

Architecture · Healthcare · Gaming · Data Platforms

The production problem

Great models aren’t enough. Production AI needs control.

You ship something that works. A prompt shifts. A model updates. Costs spike. Behavior drifts. By the time you notice, your users already have.

That's the production gap. Jixi closes it.

Clear visibility into every output and decision
Costs tracked and attributed at every step
Failures surfaced and easy to trace
Behavior stays consistent as your system evolves

Observable. Constrained. Reversible.

One layer that makes AI behavior manageable.

Swap models, update prompts, change workflows, add data. Jixi makes every change visible, measurable, and safe to deploy so your team can move fast with confidence.

Observe everything

Every step. Every decision. Every dollar.

Full execution traces across inputs, outputs, tool calls, latency, and failure points. You always know exactly what your AI did and why.

Constrain execution

Guardrails that run before failure does.

Cost caps, token budgets, and execution timeouts enforced at the workflow level. Bad runs stop early. Production stays clean.

Promote safely

Ship changes like they matter.

Version every workflow, isolate changes by environment, and roll back in seconds when behavior doesn't match expectations.

Core capabilities

Visibility, validation, and control in one operating layer.

Jixi is a production runtime. Engineering and operations teams use it to keep AI systems stable, auditable, and safe to iterate on.

Workflow runtime

AI systems, built and run as workflows.

Define each step: what to call, what to retrieve, what logic to apply. Combine deterministic behavior with agentic decisions, and connect to your data and APIs.

Every execution generates a complete record automatically — inputs, outputs, cost, latency, and failure points — so you always know what your system did and why.

Jixi workflow runtime interface

Execution observability

See exactly what your AI did, and why.

Every execution logged step by step: inputs, outputs, tool calls, cost, latency, and failure points. Debug faster. Audit confidently. Know what's running in production before your customers tell you something's wrong.

  • End-to-end execution traces
  • Per-step cost and latency breakdown
  • Failure analysis with full context

Versioned release flow

Iterate without gambling on production.

Dev, staging, and live environments with safe promotion paths between them. Every change is scoped, reviewable, and instantly reversible, the same discipline you'd apply to any critical system.

  • Dev, staging, and live environments
  • Deliberate promotion with environment isolation
  • Instant rollback on any workflow version

Confidence score

A measurable signal before every deployment.

Every Jixi workflow earns a confidence score based on structured test results. Run defined inputs against expected outputs using exact checks, LLM evaluation, or both. Get a clear read on quality and consistency before you ship.

Quality

Quantified output reliability, not gut feel.

Release gate

A real go/no-go signal before promotion.

Iteration

Change faster because you can measure what changed.

Confidence score 94 Ready for staged promotion
Structured tests
LLM evaluation
Output consistency
Jixi testing and confidence evaluation interface
Built-in data layer Safe by default
Jixi data layer and retrieval interface

Built-in data layer

Bring your data in. Keep it under control.

Files, databases, APIs, and external tools all connect through Jixi. Every access is scoped, every call is controlled, and every interaction runs inside the same execution boundary.

Ingestion

Upload and process documents across formats.

Connected data

Query databases and call APIs at runtime.

Scoped access

Limit access by workflow, environment, or customer.

Safe by default

De-identification and controls applied before model access.

Production RAG, plus everything around it.

Prompt management

Prompts shape AI behavior. Make them visible across your organization.

Prompts are part of how your AI behaves in production. Jixi makes them shared, versioned, and easy to update across workflows so teams can understand what changed, measure the impact, and keep behavior aligned as the system evolves.

Visibility

See the prompts shaping behavior across every workflow.

Version history

Track every prompt change with rollback-ready history across the system.

Reusable templates

Standardize prompt patterns your teams can reuse without rewriting from scratch.

Prompt changes become visible system changes, not hidden edits.

Prompt management Shared behavior layer
Jixi prompt management interface

Move fast. Stay in control.

Built for agents.
Backed by a controlled runtime.

Agents move fast. Jixi keeps it under control. Workflows, tests, and releases run inside defined bounds, with full visibility and safe promotion at every step.

01

Build with agents

Use Claude, Cursor, or Codex to generate workflows, test suites, and prompts. Agents draft the structure; you review and ship.

02

Define everything as code

Workflows, tests, prompts, and data live in simple config files. Version, review, and update your system the same way you manage infrastructure.

03

Run in a controlled runtime

Every execution is tracked, versioned, and scoped to environments. Changes are visible, measurable, and safe to promote.

jixi.yml Jixi as Code
schemaVersion: "1"
app:
  name: Student Redesign
  environments:
    - name: live
      color: "#2cb652"
    - name: staging
      color: "#FD5102"
workflows:
  - name: Add Students
    apiId: add-students
    steps:
      - name: Load Prompt
        type: load_prompt
        config:
          promptName: Add Students
          version: latest
          overrides:
            grade_level: "{{ input.body.grade_level }}"
            school_type: "{{ input.body.school_type }}"
      - name: Generate Image
        type: generate_image
        config:
          model: fal-ai/nano-banana-2
    aliases:
      live: v3
      staging: v2
  - name: Apply Color Palette
    apiId: apply-color-palette
    steps:
      - name: Get Extended Prompt
        type: custom_code
        code: |-
          async function execute(body, context) {
            const level = body?.answers?.level || "";
            return { prompt: `Apply: ${level}` };
          }

Teams

Shared control across engineering, product, and operations.

Jixi gives every team the same runtime truth: what changed, how it behaved, what it cost, and whether it is safe to promote.

Engineering

Version behavior like critical infrastructure.

Trace execution, compare releases, and roll back the moment a workflow stops behaving the way it should.

Product

Measure quality before a release reaches users.

Use replay traffic, evaluation, and confidence scoring to validate whether changes actually improve outcomes.

Operations

Keep spend, latency, and drift visible.

Run AI inside defined budgets and runtime boundaries instead of discovering instability after deployment.

Ready to ship?

Stable AI systems don't happen by accident.

Jixi gives teams the control layer to manage AI behavior as models, prompts, and data keep changing beneath them.