Production AI runtime

The runtime layer
for production AI.

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

Start building See how it works

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.

Data Platforms

Turn data into answers. Reliably.

Jixi connects AI workflows directly to your data sources, enabling systems that extract, analyze, and respond with structured outputs. From internal tools to external APIs, everything runs within a controlled runtime.

Use cases

AI-powered reporting and analytics
Knowledge assistants over internal data
Automated insights and summaries
Agentic workflows across APIs and databases

Why Jixi

Native integrations with APIs, databases, and MCP servers
RAG built into workflows with scoped data access
Agentic workflows that plan, retrieve, and respond
Full observability into how answers are generated

Data-driven AI systems you can actually trust in production.

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.

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

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

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.

Build with agents

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

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.

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: 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.

Start building Explore the platform

The runtime layer
for production AI.