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Effektiv Platform
EffektAI

The Agentic Development Platform

Every Effektiv engagement runs on EffektAI. The same eval rig framework, agent mesh, and AU governance layer — tested across sixteen production SaaS products and shipped to every client at exit.

When the method lives in a platform rather than a slide deck, quality ships consistently. When the platform ships to your team at exit, the value stays with you — not us.

Talk to us about EffektAI See the platform →

73%

of code AI-authored on production engagements — every line traceable to an agent, prompt, and model version

5

eval gates on every pull request before a human sees the diff — spec, test, security, performance, trace

16

production SaaS products built and running on EffektAI — $1.1M against a $4.2M Big-4 quote

0

platform components retained by Effektiv at exit — eval rig, trace database, runbooks, prompt rules all yours

See EffektAI in action

How the platform turns a brief into production code.

Coming soon · EffektAI platform walkthrough

Video placeholder — production to follow

A full platform walkthrough is in production. Request a live demo →

The platform thesis

A method in a slide deck degrades. A method in a platform ships consistently.

Most software consulting firms have a delivery method. It lives in a deck, a SharePoint page, or the heads of two or three experienced practitioners. When those practitioners aren't on your account, the method isn't either.

EffektAI encodes the Effektiv delivery method into a platform — the eval rig framework, the agent orchestration layer, the AU governance controls, and the authorship trace system. Every engagement runs on the same tested stack. Quality doesn't depend on which pair is assigned to your account.

The second and more important difference: EffektAI ships to your team at exit. The eval rig code, the trace database, the runbooks, the prompt rules — everything transfers. You are not dependent on Effektiv to run what we built. That is the commercial model, not a feature toggle.

When the method is a platform, it ships consistently regardless of which senior pair is on your account. That is the difference between a consulting firm and a software services company with defensible value.

Ashiq Rahman · Founder, Effektiv

Traditional method

  • Lives in a deck or SharePoint doc
  • Depends on assigned practitioners
  • Degrades between engagements
  • Stays with the vendor at exit

EffektAI

  • Encoded in a tested platform
  • Consistent across every engagement
  • Improves with each production run
  • Ships to your repo at exit

Platform capabilities

Six layers. One integrated platform.

Each capability solves a distinct problem in AI-augmented delivery. Together they form the platform that makes EffektAI more than a method.

🔍

Layer 01

Diagnose Engine

AI agents read codebases, sprint history, incident logs, and production data. They surface undocumented fields, hidden dependencies, and load-bearing rules that documentation has never captured — before a single line of rebuild code is written.

  • Codebase archaeology across any language or stack
  • Data-led discovery — reads the data, not just the docs
  • Output: findings document + fixed-fee Design proposal
🧪

Layer 02

Eval Rig Framework

Multi-gate evaluation runs on every pull request. Five gates — spec coverage, test coverage, security scan, performance budget, authorship trace integrity — fire before any human reviewer sees the diff. Outputs that fail do not merge.

  • Gates defined in Design, not improvised at exit
  • Runnable source code ships to your repo at handover
  • Extended by your team after we leave
🤖

Layer 03

Agent Mesh

Coordinated AI agents handle the work that benefits from breadth and speed — code authoring, test rebuilds from runtime traces, migration scripts, eval scaffolding, and integration adapter generation. Humans own the decisions that require judgement.

  • Build, test, migrate, and triage agents in coordination
  • Money writes and records of truth always human-gated
  • All inference on AWS Bedrock AU regions, no sovereignty issue
🗄️

Layer 04

Authorship Trace System

Every line of AI-authored code is attributed to an agent, prompt revision, and model version. The trace database is queryable on demand and ships to the client at exit. For regulated clients, the audit pack a regulator asks for runs directly from this trace.

  • Per-PR trace: agent, prompt rev, model version, eval gates
  • Audit-ready for APRA, AHPRA, Privacy Act regulated clients
  • Database ships to your repo — owned by you at exit
🏛️

Layer 05

AU Governance Layer

Regulatory controls for AU mid-market, enterprise, and government are baked into the platform — not added as a checklist after delivery. APRA CPS 230, NIST AI RMF, the AU AI Voluntary Safety Standard, and Privacy Act APP 1.7 audit-log requirements are mapped in Design and enforced at runtime.

  • APRA CPS 230 · NIST AI RMF · AU AI Safety Standard
  • IRAP pathway for government PROTECTED data (Q4 2026)
  • Named human accountable on every autonomous decision
🔄

Layer 06

Continuous Delivery Loop

After handover, the platform your team owns keeps working. Eval rig gates catch regressions. The authorship trace records every future change. The runbooks capture how the system actually behaves in production — not how it was designed to behave. Your systems stop aging by default.

  • Post-handover eval gates run in your own CI pipeline
  • Runbooks updated from production resolution data
  • Extend with new agents without re-engaging Effektiv

Built for the full SDLC

From legacy codebase to production system — EffektAI spans every phase.

Thoughtworks' AI/works™ defined this model at enterprise scale. EffektAI is the same idea built for the AU mid-market at a fraction of the price — and with no lock-in.

01

Ingest

Diagnose Engine reads legacy code, data, and incident history. No documentation required.

02

Specify

AI generates the architecture, eval gates, and outcome contract from what Diagnose found — not from a template.

03

Build

Agent mesh authors code under human review. Five eval gates on every PR. 73% AI-written, 100% human-approved.

04

Ship

Cut-over rehearsed in a model copy of the production stack. Rollback gates defined. Your team runs the production switch.

05

Operate

Triage agents, eval gates, and the resolution database keep running in your repo. Continuous delivery without re-engaging us.

EffektAI runs on AU-region infrastructure from

AWS Bedrock Sydney Anthropic Claude (AU infra) Google Gemini (AU region) AWS VPC · IAM · PrivateLink · KMS Model-agnostic — no hyperscaler lock-in AWS Bedrock Sydney Anthropic Claude (AU infra) Google Gemini (AU region) AWS VPC · IAM · PrivateLink · KMS Model-agnostic — no hyperscaler lock-in

Common questions

Frequently asked questions.

Built on EffektAI. Yours at exit.

See EffektAI applied to your next engagement.

Show us a scope, a legacy system, or an integration estate. We price on outcomes, deliver on EffektAI, and hand the platform components to your team when we leave.