See, control and improve how AI builds your software.
AI agents across your SDLC, with governance and full visibility built in. Keep the coding tools your developers like — Sage turns tickets into reviewed pull requests the same way on every team.
// 5 design-partner spots open · personal onboarding included
// sage runner · run #4831complete
Add requirement · catalogue · story 3
retail-platform-v3 · PLAT-453 · workflow: Add New Requirement v1.5
elapsed
5m 52s
ai cost
$0.058
tokens
8,070
hitl gates
2 / 2
// agent pipeline · live
✓
Input Assessment Agent
assessment · input-assessment/v2.1
doneClaude Code · haiku-41m 12s · 1,240 tok · $0.008
✓
Story Decomposition Agent
decomposition · story-decomp/v1.5 · HITL
doneClaude Code · sonnet-43m 18s · 4,210 tok · $0.024
✓
Story Quality & DoR Agent
critic · story-quality/v1.2
doneAutoGen · haiku-452s · 1,980 tok · $0.019
✓
Linear Writeback Action
action · connector: linear · risk: LOW · HITL
doneBedrock30s · 640 tok · $0.007
awaiting you
// you're the reviewer — approve to continue
Run complete · 5 stories written to Linear
Every step traced: inputs, prompt version, model, engine, tokens, cost and who approved.
from the Sage Runner demo · time compressed
// 01 · the question we hear most
Your developers already use AI. So why does every team still ship differently?
Coding agents make your best developer faster. Sage makes your whole team deliver the way your best developer would — with the cost, audit and control leadership needs.
// 02 · is sage right for you?
Too big for ad-hoc AI. Too small to staff an AI platform team.
<20
20–50
50–100
100–200
200+
You probably don’t need Sage yet.
Start with our free guide to using AI coding tools well. Come back when teams start working in different ways.
// free guide → learn
We’re your AI R&D team.
You focus on the product. We keep your AI tooling current, tested and working — without you hiring for it.
// usually: pilot → sage.resident
One way of working with AI, across every team.
Shared workflows, gates and prompts, so quality stops depending on who happens to be on the project.
// usually: pilot → sage.studio
Full visibility and control over AI at scale.
Cost per team, audit trails and approval gates that leadership — and your clients — can rely on.
// usually: pilot → sage.studio, then sage.resident alongside your platform team
Let’s talk scope.
We can start with one team or one workflow and grow from there.
// usually: a focused pilot with one team
// 03 · what changes
Three things change when your team runs on Sage.
review-rubric v3.0review-rubric v3.1 · approved · rolled out to all teams
Your organisation owns how AI is used
Which models run, which prompts and skills apply, which gates are enforced — decided once, centrally, and applied everywhere.
memory · confirmed learningsrun 1 → run 50 → run 200: corrections stop repeating
Quality and knowledge compound
Every run draws on confirmed knowledge of your codebase and past decisions — and it stays with you when people move on.
engine: current → candidateevaluated on your workflows · swapped once · applied to all
Tools change. Your workflows don't.
When a better tool or model arrives, it's tested on your work and rolled out once — no relicensing, retraining or re-platforming.
// 04 · how it works, in one rule
Nothing calls a model or your systems directly.
Model calls go through Model Rail. Actions go through Tool Gateway. That single rule is what makes cost control, audit and tool replacement possible.
// hover any block for a plain-English note
// who uses it
Leadership
Engineering leads
Developers
↓
// sage — the governed system
Runnerworkflows & gates
Runs each workflow step by step, applies your rules, and routes approvals to the right people.
Prompt & Skill Storeversioned assets
Agent definitions, skills and prompts kept as versioned assets — improved, rolled out and rolled back centrally.
Critic & Evalsquality scoring
Scores every output against a scorecard before a person sees it, and tests changes before they go live.
Memoryruns · learnings · codebase
Recent runs, confirmed learnings and a structured map of your codebase — so context isn't re-explained.
Observabilitytraces & audit
Traces every run end to end for debugging, audit and reporting.
HOLD · Sep 2026Letting every developer install MCP servers: why we'd wait
// 07 · what changes for you
Today, and with Sage.
todayAI spend arrives as vendor bills, with no link to projects or delivered work.
with sageEvery model call is attributed to a team, project, workflow and run.
todayLittle record of what AI produced, from which inputs, or who reviewed it.
with sageEvery run is traced end to end — inputs, model, prompt version, approvals.
todaySensitive code and client projects limit where AI can be used.
with sageRuns managed, in your cloud or on-premises, with the models you choose.
todayEach developer picks a model, or the vendor decides. No policy.
with sageModel policy set once and applied on every call, across providers.
todayInstructions scattered across tool-specific files and personal setups.
with sageAgents, skills and prompts versioned, evaluated and rolled out to every team.
todayGood practice varies from team to team.
with sageWorkflows with standard steps, gates and scorecards, configured per team where needed.
todayThe same context is re-explained every session.
with sageAgents draw on confirmed knowledge of your codebase and conventions.
todayReviewers spend time catching avoidable issues.
with sageThe Critic scores every output before a person sees it.
todayAI work gets copied by hand into tickets and repos.
with sageWork arrives as pull requests where you already work. Keep your preferred tools.
// 08 · to set expectations
What Sage is not.
An IDE replacementDevelopers keep their editor and tools.
Autonomous deploymentPeople approve and merge. Always.
Another modelModel-agnostic. Uses the models you choose.
Install-and-forgetConfigured to your process, with us alongside.
// 09 · how we work together
Prove it on one workflow. Then choose your path.
step 1 · everyone starts herePilotOne real workflow on your codebase, run in our environment alongside your current tools. We compare quality, review effort, consistency and cost.[PILOT LENGTH] · in our environmentScope a pilot
step 2 · then choose one →
sage.studioSage in your environment. We build defined workflows, hand them over, and you run them.// you know the outcome you want
or
sage.residentSage in your environment, with an embedded engineer who sets up workflows, integrations, agents and projects.// you have a roadmap and need people to execute it
// 10 · proof, not promises
Built by senior engineers and architects who ship software for a living.
We’d rather show you a real run than a logo wall. Every Sage run leaves a trace like this one — and the pilot gives you dozens on your own code.
5 design-partner spots openPilot in our environment · production in yours
// step-by-step trace · run #4831 · sage runner demoworkflow add-new-requirement v1.5 · PLAT-453trigger linear webhook · label: agent:add-requirementstep 1 input-assessment/v2.1 · claude code · haiku-4 1m 12s · 1,240 tok · $0.008 · donestep 2 story-decomp/v1.5 · claude code · sonnet-4 3m 18s · 4,210 tok · $0.024 · hitl: any_approveroutput 5 stories drafted · 1 flagged over 8ptgate sla 15 min · awaiting approvalcost $0.032 so far · est. $0.058 on complete
// next step
Start with one real workflow.
A focused pilot on your codebase, run alongside your current tools. No commitment beyond it.