The control plane for AI-native engineering

Different tools. One engineering system.

Run engineering on AI, from roadmap to release, across every team.

Q4 roadmap → this cycle3 teams · 3 harnesses · one system
Single sign-on for admin Billing on v2 Faster mobile checkout
Planned 1
PAY-18Payments
Billing API contract
CodexPlanned
Building 1
PAY-15Payments
Webhook retry queue
CodexDeveloper agent
In review 1
MOB-7Mobile
Offline cart sync
CopilotWaiting on a person
Shipped 1
PLT-39Platform
Rate-limit the public API
Claude CodeShipped ✓
✓Plan approved by the tech lead
✓Claude Code, Codex, Copilot ✓Human-in-the-loop ✓Full audit trail

Why Wakalix

AI made coding faster. Running engineering didn't get easier.

Four challenges come with scaling AI. Wakalix answers each one.

Faster code, same slow delivery

Planning, review and release still move at human pace.

WakalixRuns the whole cycle, not just the coding.

AI spend with no link to outcomes

Bills grow; nobody knows which work they paid for.

WakalixEvery item estimated first, tracked per item and team.

New security risks, few controls

Secrets, customer data and injected instructions pass through unchecked.

WakalixGuardrails, human approval and an audit trail, by default.

No insight for leaders

What shipped, and was it worth it? Nobody can say.

WakalixOne live view of delivery, cost and quality.

How it works

From roadmap to release, in one system.

People decide. Agents do the heavy lifting. Every step is on the record.

1Roadmap

Start from what the organisation intends to build.

Every product keeps a ranked roadmap, and every cycle traces back to it.

People set direction
Roadmap
The Wakalix roadmap: ranked items per product, each marked proposed or accepted.
Product screen · the roadmap
2Plan & approve

A plan, sized and assigned — approved by a person.

Each item gets a definition of done and the right agent. Nothing runs until a person approves.

A person approves
Cycles › New tax year rates
A delivery cycle in Wakalix: plan, execute and retro phases, the approved plan, and the board — one item blocked because an agent asked a person.
Product screen · a cycle, its approved plan and its board
3Context

Every task starts with the right context.

The ask, the code that matters, your rules and past decisions, packaged for the agent.

Context engineering
The ask and its definition of doneRelevant code, from a scan of your repoYour standards and rulesDecisions already on recordThe agent's own instructions
Context packagebuilt for this one task
Claude CodeCodexCopilotyour engineers' harness
4Build

Agents build it — and stop to ask when the call is yours.

Each agent has a defined job and runs in your engineers' own tool. When a decision is yours, it stops and asks.

Human-in-the-loop
B-3 · Design the deduction rate model
An architect agent asking a person for a decision: two ways to model a rate, the trade-off of each, and a note that nothing has been written until somebody answers.
Product screen · an agent asking a person for a decision
5Review & accept

Checked against its criteria. Accepted by a person.

Work comes back with its evidence, and lands as a pull request a person merges.

A person accepts
B-1 · Survey the existing deduction paths
A finished work item: the commit, branch and repository it produced, each acceptance criterion marked met, and a note that a person accepted it.
Product screen · what came back, checked and accepted
6Release & learn

Every cycle makes the next one better.

The retro feeds what agents got wrong back into them, so each cycle starts from a better team.

Agents improve
Reports › Delivery
The delivery report by cycle: items planned and done, how often an agent asked a person, and the time each cycle took to close.
Product screen · the delivery report, by cycle

Many teams, one system

Every team works its own way. You see one system.

Teams keep their own tools, agents and rhythm. Leadership gets one roadmap, one record, and one answer on cost.

PaymentsCodex
Rhythm
Weekly cycles
Agents
DeveloperReviewerCompliance checker
Rules
Two approvers on anything touching money
PlatformClaude Code
Rhythm
Continuous, small items
Agents
ArchitectDeveloperMigration agent
Rules
Architect signs off every schema change
MobileCopilot
Rhythm
Two-week cycles
Agents
DeveloperReviewerUX reviewer
Rules
Release notes on every change

Highlighted: agents a team built itself

  • 01
    What shippedItems accepted and cycles closed, by team.
  • 02
    What it costEstimated before you approve it, measured from your own subscriptions as it runs.
  • 03
    Right first timeHow often work was accepted first time.
  • 04
    Your people's timeHow many decisions AI asked of your people.
Portfolio › Proof
A quarterly proof page: work items accepted, cycles closed, tokens consumed from the organisation's own subscriptions, first-attempt acceptance rate and hours of human decision time.
Product screen · the quarterly proof page · where the spend goes →

Agents you own, governed by default

A prompt is a sentence. A Wakalix agent is a governed asset.

Defined once, owned by you, released like software, and held to your rules whether the model remembers them or not.

Developer agent · v3Owned by the Platform team · pinned for every team
  • RoleWhat it's for
  • SkillsThe jobs it can do
  • ToolsWhat it may use
  • ContextWhat it reads first
  • GuardrailsRules outside the model
  • Hand-offsWho it works with
  • CheckpointsWhere a person decides
  • VersionsReleased and pinned
  • EvalsTested before release

Build your own in the agent builder; every version passes its evaluations before release. More than spec-driven development →

Your rules hold even when the AI forgets them: most are built into how work moves, so they can't be skipped. Only real judgement calls go to the AI.

Work arrives as a pull request a person merges.

Built in

Every change says which requirement it serves.

Built in

A plan runs only after a person approves it.

Built in

Schema changes need the architect's sign-off.

A named person signs off

Keep changes small and focused.

AI judgement
Rules
The rules registry: each rule, how it is enforced, and what it costs the model - most of them nothing.
Product screen · the rules registry

Built for the security review, not in spite of it: leaked secrets, injected instructions and unreviewed changes, closed by default.

Never runs the model

Code reaches only the AI provider you approved.

Your keys stay yours

Agents use each engineer's own access. No shared keys.

Human-in-the-loop

A person accepts every change before it lands.

Secrets and PII kept out

Output is checked for credentials and personal data.

The twelve questions a security review asks → · request our security pack

Pricing and access

Flat, predictable, and on the page.

Per team of up to eight, per month. More teams, lower price each. Your AI subscriptions stay yours.

Most teamsProBuild and own your AI team.
₹39,000
per team, per month
  • The starter agents, ready to work
  • Roadmap, cycles, reviews and the audit trail
  • Create and version your own agents
  • Evaluate every version before release
  • Onboarding, and a shared support channel
EnterpriseEverything, plus what security and audit teams need.
₹55,000
per team, per month
  • Everything in Pro
  • Access rules per repository and person
  • Access-review export for auditors
  • Run agents on your own endpoint
  • A named contact, faster response

Tell us about your engineering organisation. A person replies in 10 minutes, 9am–7pm IST, Monday to Friday.

Every plan: SSO with your identity providerThe full audit trailSupport 9am–7pm IST, Monday to Friday