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OFFERING

AISDLC Advisory & Enablement

AISDLC is an AI-native lifecycle with evaluation, governance and model economics built into every stage, from requirements to production. This engagement brings it into your team's process.

The approach

AISDLC is how we engineer intelligent systems — and this engagement brings it to yours, end to end: from the decisions that shape the system to the machinery that keeps it correct, governed and economical in production.

We build these systems ourselves, so the advice is grounded in what we ship. The enablement is engineering in your codebase, and your team keeps the practices and reference implementations.

What you get
—Evaluations that gate releases
—Guardrails & full lineage
—Right model, right cost
·WHAT WE BUILD

Inside AISDLC Advisory & Enablement.

01

Model & architecture strategy

We help you decide build vs buy, open vs commercial, and where fine-tuning earns its place.

Build vs buyopen vs commercialfine-tuning
02

Evaluation

We define what “good enough to ship” means, then build the evaluation pipelines and gates that enforce it.

Golden setsrubricsquality gatesregression
03

Orchestration & routing

We route work across model tiers so cost, latency and quality are decided per task.

Multi-model routingtieringfallback
04

Governance & guardrails

We wire policy, guardrails, traceability and compliance into the lifecycle — audit-ready by design.

Policy enforcementguardrailslineagecompliance
05

Observability & MLOps

Every path is instrumented, so behaviour, drift and cost are measured.

TelemetrytracingMLOpsdrift detection
06

Economics

We make model choice an operating decision: the right model per request, at the right cost.

RoutingtieringAI Tokenomics

Representative work Evaluation, orchestration and governance for production AI — grounded in AISDLC. See case studies →

·HOW TO ENGAGE

How an engagement runs

The steps of the engagement, and how we charge for them.

01

AISDLC assessment workshop

We map how you build today — your lifecycle end to end, from requirement gathering to delivery — and where AI does and doesn't yet fit your process.

02

Find the gaps

We identify where evaluation, governance, model-routing economics and observability are missing or weak in your current lifecycle.

03

Wire it into your lifecycle

We build the practices into your process and codebase: evaluations and quality gates, guardrails and lineage, model routing and telemetry, with reference implementations your team owns.

04

Adopt & own

Your team runs it inside its own lifecycle: the practices, the gates and the reference implementations.

How we charge

Starts with a fixed-fee assessment workshop. Enablement is delivered as a scoped, time-boxed engagement; teams that want continued support move to a light advisory retainer.