TURION .AI
SYS / RUNTIME v 4.21.0 · STABLE N / 38°54′ W / 77°02′
PLATFORM · v4 · GENERAL AVAILABILITY

AI agents for
autonomous work.

Turion plans, deploys, and operates AI integrations for companies — built on the SDKs your team already runs and shipped through the CI you already trust.

runtime.observe()
AGENTREGIONp95STATUS
agent.support-tier-1 us-east-1 312ms OK
agent.research-deep eu-west-1 1820ms OK
agent.sdr-outbound us-west-2 188ms OK
agent.rfp-architect us-east-1 902ms WARN
agent.kb-indexer eu-central-1 65ms OK
● live · 5 of 1,284 agents refresh 1s
↓ INDEX 01 / 09
§ 02 HOW WE WORK

Scan. Deploy.
Monitor.

We work with companies end-to-end: from introducing AI and finding where it fits, through deploying the first agents, to keeping them healthy in production.

/ 01

Scan

Free scan of your stack and your workflows. We hand back a PDF report mapped to a four-level adoption ladder, with a ranked list of agents to ship next.

  • Free · 1–2 weeks
  • L1→L4 adoption ladder
  • Ranked, costed shortlist
READ THE BRIEF
/ 02

Deploy

Per-agent build, priced for SMBs. From $500/agent for simple work; complex agents quote higher in writing before we start. Source under your repo from day one.

  • From $500 / agent
  • Vercel · Claude · OpenAI · Google
  • Eval suite + 30-day support
READ THE BRIEF
/ 03

Monitor

Monthly retainer that keeps the deployed agents healthy. CI/CD, evals on every change, model migrations on a quarterly cadence, on-call humans for hard errors.

  • From $250 / month
  • GitHub Actions · GitLab Agents
  • Quarterly model migrations
READ THE BRIEF
§ 03 STANDARDS

Industry standards.
Built for production.

We work with the current industry-standard SDKs to build robust AI agents in production. Pick whichever one your team already knows — we ship through the CI/CD pipeline you already trust, and the runtime underneath stays boring on purpose.

/ build · 4 sdks choose one per agent

Vercel AI SDK

Vercel · TypeScript

Default when the agent ships inside an existing Next.js or Node app and the team wants the runtime co-located with the rest of the product.

import { streamText } from "ai";
import { openai } from "@ai-sdk/openai";

const result = await streamText({
  model: openai("gpt-4.1"),
  prompt: ticket.body,
  tools: { searchKb, jiraCreate },
});

Claude Agent SDK

Anthropic · TS / Py

First-class agent loop with tools, file editing, and bash. Picked when the work is multi-step reasoning, code, or long-context document workflows.

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();
const stream = client.messages.stream({
  model: "claude-opus-4-7",
  tools: [searchKb, jiraCreate],
  messages: [{ role: "user", content: ticket.body }],
});

OpenAI SDK

OpenAI · TS / Py

Responses API and function calling. The right pick when the team is already on the OpenAI stack or needs the managed runtime + web search out of the box.

from openai import OpenAI

resp = OpenAI().responses.create(
    model="gpt-4.1",
    instructions="You triage tickets for Acme.",
    input=ticket.body,
    tools=[search_kb, jira_create],
)

Google ADK

Google · Python

Model-agnostic Agent Development Kit centred on Gemini and Vertex. Picked when the data, IAM, and observability already live in GCP.

from google.adk.agents import Agent
from google.adk.runners import Runner

agent = Agent(
  name="triage",
  model="gemini-2.5-pro",
  tools=[search_kb, jira_create],
)
Runner(agent).run(ticket.body)
/ ship · 3 pipelines whichever your team already runs

GitHub Actions

GitHub · CI/CD

Standard install · lint · eval · deploy workflow. Every promotion runs the regression suite and posts the delta on the PR before a human merges.

# .github/workflows/deploy.yml
jobs:
  ship:
    runs-on: ubuntu-latest
    steps:
      - run: pnpm install
      - run: pnpm eval --gate 0.92
      - run: pnpm deploy --env prod

GitHub Agentic Workflows

GitHub · agentic CI

Agentic steps inside CI. Triages failed eval runs, drafts postmortems, and grades PR diffs against the agent's expected behaviour before they reach prod.

# .github/workflows/eval-grade.yml
jobs:
  grade:
    steps:
      - uses: anthropics/claude-code-action@v1
        with:
          prompt: "Grade eval delta vs main."

GitLab Agents

GitLab · CI/CD

Same shape as the GitHub workflow, on the runner pool your team already operates. Picked when GitLab is the company default.

# .gitlab-ci.yml
ship:
  image: turion/agentic-runner:1
  script:
    - npm ci
    - npm run eval -- --gate 0.92
    - npm run deploy -- --env prod
§ 04 AGENT FLEET

Agents in production.

Six of the agents currently running for design partners. Each one shipped, instrumented, and on-call.

§ 05 DEVELOPERS

Real SDKs.
Real CI.

No bespoke runtime, no proprietary DSL. The agent is an SDK call you can read in twenty lines. The deploy is a workflow file your team already maintains. You can fire us on a Friday and ship on a Monday.

~/agents/triage.ts
import { generateText, tool } from "ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";

// One agent. One SDK. Tools your team already wrote.
const result = await generateText({
  model: openai("gpt-4.1"),
  system: "You triage support tickets for Acme.",
  prompt: ticket.body,
  tools: {
    searchKb: tool({
      description: "Search the support knowledge base.",
      inputSchema: z.object({ query: z.string() }),
      execute: async ({ query }) => kb.search(query),
    }),
    jiraCreate: tool({
      description: "Open a Jira ticket when escalation is needed.",
      inputSchema: z.object({ title: z.string(), body: z.string() }),
      execute: async (input) => jira.create(input),
    }),
  },
  stopWhen: stepCountIs(8),
});
§ 06 OBSERVABILITY

You shipped it.
Now prove it works.

Every agent decision is a span. Every span is replayable. Every replay produces a delta. We treat agent quality like SREs treat reliability.

DASHBOARD · agents.production window: 24h · region: all · n=1,284
p50 312 ms −8.2%
p95 1.42 s −4.1%
p99 2.88 s +1.2%
errors 0.04 % −12%
00:0006:0012:0018:00now
TSAGENTEVENT·VAL
12:04:11 agent.support-tier-1 span.complete OK 294ms
12:04:09 agent.research-deep tool.call OK 1.81s
12:04:07 agent.rfp-architect guardrail.hit WARN pii
12:04:06 agent.kb-indexer eval.pass OK 0.94
12:04:02 agent.sdr-outbound span.complete OK 188ms
TRUSTED BY TEAMS SHIPPING REAL AGENTS
We tried two other platforms before Turion. Both demoed beautifully and died in production. Turion shipped a working agent in three weeks and has been on the pager with us ever since. That's the part nobody else does.
Marisol Veen
VP Engineering · Halcyon Health
§ 08 PRICING

Free scan. Per-agent build.
Monthly retainer.

Sized for SMBs and enterprises alike. A free scan to see what's worth building, per-agent pricing for the build, and a small monthly retainer to keep it healthy. Token spend with the model provider stays on your account.

AI OPPORTUNITIES SCAN
Free one-off · pdf report
  • Infrastructure + process scan
  • L1→L4 adoption ladder
  • Ranked, costed agent shortlist
  • Branded PDF + readout call
Book a free scan
AI AGENT MONITORING
From $250 / month · scales with agents
  • CI/CD via GitHub Actions or GitLab
  • Eval regressions on every change
  • Quarterly model migrations
  • On-call for hard errors
Start monitoring
/ 09 · NEXT

Build the agent your
team keeps promising.

Pair with one of our solutions architects. Two weeks from kickoff to a deployed, evaluated, observable agent in your stack.

we'll walk you through a system that's already running in production