AI Consulting

In today's market, data is your most valuable asset, but only if you know how to use it. Our AI consulting services help you build a robust data foundation and leverage cutting-edge AI technologies to drive innovation, maximize efficiency, and predict future trends.

AI Consulting Services — from Strategy to Scaled Impact

Cognaify helps public sector and enterprise teams move from AI ideas to real outcomes. We combine strategy, data engineering, responsible AI, and delivery discipline to prove value quickly and scale what works.

What we deliver

Clear strategy & roadmap: Align priority use cases to business goals, operating constraints, and measurable KPIs.
Data & platform foundations: Ingest, model, and govern the data your AI needs—without upheaval.
Rapid pilots: 6–8 week sprints to test high-value use cases with success criteria agreed upfront.
Responsible AI & security: Privacy-by-design, risk controls, auditability, and human-in-the-loop guardrails.
Change & enablement: Playbooks, training, and handover so your teams can run and improve the solution.

Advisory packages

AI Readiness Assessment

Outcome: A clear understanding of your current state, key gaps, and a tailored 12-month roadmap.

What’s included: Comprehensive review of data and systems, prioritised use-case funnel, benefits vs. effort sizing, quick-win plan, and risk register.

Use-Case Discovery

Outcome: Identification of 3–5 high-value use cases tailored to your business context.

What’s included: Value hypotheses, data requirements, acceptance criteria, measurable success metrics, and governance & risk considerations.

Pilot Sprint

Outcome: A production-ready beta of one priority use case.

What’s included: Data pipelines, baseline model development, user interface/alerts/integration, testing, success reporting, and knowledge handover.

Scale & Operate

Outcome: Sustainable, repeatable delivery with reliability and trust.What’s included: MLOps framework (monitoring, retraining, rollback), performance dashboards, governance controls, runbooks, and value-tracking mechanisms.

AI governance & security

Responsible AI: Purpose limits, bias checks, human oversight, transparency notes.
Privacy & compliance: Data minimisation, encryption, consent patterns; aligned to Australian regulatory expectations.
Model & data security: Access controls (RBAC/ABAC), audit logs, adversarial testing, incident runbooks.

Data & platform foundations

Integration & ingestion: APIs, event streams, batch connectors into a lake/warehouse you control.
Feature store: Reusable features (e.g., risk scores, behavioural patterns) for faster iteration.
MLOps: Model registry, CI/CD, monitoring for drift/quality, and A/B evaluation.
Dashboards & APIs: Operational views for teams; clean interfaces for partners and downstream apps.

Where we’re strongest

Local & state government: citizen services, case/complaints, regulatory compliance, readiness programs.
Utilities & councils: field safety, asset insights, carbon and sustainability reporting.
Agri & supply chain: biosecurity risk, traceability, inspections, verification workflows.
Data governance & MDM: Customer 360, catalog/lineage, policy automation, data quality.