Beyond Now and Business AI partner to deliver vendor-agnostic, scalable enterprise AI in South Africa
Beyond Now will power Business AI's enterprise marketplace in South Africa, giving large organizations a governed, vendor-agnostic way to build, test, and scale AI solutions. The goal is straightforward: move from isolated proofs-of-concept to production systems that ship value, avoid lock-in, and meet compliance needs.
Business AI, a Mustek subsidiary, has already pulled in support from 16 major enterprises including Woolworths, Bidvest, and Stefanutti Stocks. The operating model combines a proven deployment framework with a closed marketplace where trusted partners co-develop and co-sell solutions under shared standards.
Why this matters for IT and development teams
Executives are frustrated with AI ROI-only a small fraction of projects deliver. The approach here is to standardize how AI gets adopted: clear guardrails, open supplier choice, and measurable outcomes.
- A proven framework for repeatable AI deployments
- A vendor-agnostic environment-choose preferred suppliers and LLMs without lock-in
- An ecosystem of relevant services, use cases, and hardware
- A closed, governed marketplace for building, trialing, and sharing successful solutions
How the marketplace works (technical view)
Think of this as an orchestration layer and catalog for enterprise-grade AI building blocks. It abstracts model choice, infrastructure, and partner services behind policy, templates, and automation.
- Solution templates with reference architectures (RAG, agentic workflows, predictive pipelines)
- Model abstraction: swap LLMs or vision models without reworking the whole stack
- Integration points: feature stores, vector DBs, data catalogs, and CI/CD
- MLOps pipelines: gated promotion from sandbox to staging to production
- Security and compliance guardrails: RBAC, scoped secrets, audit logs, lineage
- Observability: model evaluation, drift alerts, latency/SLO tracking
- Commercialization: billing, entitlements, and revenue share for partner-built solutions
Why vendor-agnostic matters
Different use cases favor different models and infrastructure. The ability to switch providers for cost, quality, or policy reasons is a practical advantage, especially under changing licensing or token economics.
- RAG with swappable LLMs across providers; keep your vector and retrieval layer stable
- Event-driven AI automations that tie into existing service buses and data platforms
- Computer vision pipelines with pluggable models and hardware acceleration options
- FinOps controls: per-workspace budgets, cost telemetry, and kill-switches
The closed marketplace creates a trusted environment for co-development and reuse across large enterprises and tier-one partners-without handing the keys to a single vendor.
Governance and risk management
The framework prioritizes responsible AI with clear operational controls. Expect policy-as-code, dataset access control, PII detection, consent management, and human-in-the-loop where risk demands it.
- Model risk tiers mapped to deployment requirements and review cadence
- Dataset lineage and approvals with retention and residency policies
- Evaluation gates: bias checks, toxicity, factuality, and safety tests
- Incident response playbooks and rollback procedures
- Audit-ready logs for regulators and internal assurance
For teams building internal standards, the NIST AI Risk Management Framework is a solid reference point. See the NIST AI RMF. South African teams should also align with POPIA guidance via the Information Regulator.
A practical 90-day adoption plan
- Weeks 0-2: Inventory top 5 use cases. Map data sources, risk levels, and success criteria.
- Weeks 2-4: Stand up the marketplace tenant. Configure RBAC, secrets, policies, and audit.
- Weeks 3-6: Select model candidates per use case. Define evaluation suites and baselines.
- Weeks 4-8: Build two POCs using solution templates. Wire up feature/embedding stores.
- Weeks 6-10: Run A/B comparisons, cost tracking, and red-team tests. Close gaps.
- Weeks 8-12: Promote one POC to production with SLOs, alerts, and on-call runbooks.
Questions to ask before you commit
- Can we change models or infrastructure without refactoring the entire solution?
- What guardrails enforce data residency, least privilege, and model evaluation?
- How are usage, cost, and performance tracked per workspace and solution?
- Is there a clear path from sandbox to prod with approvals and audit trails?
- How does the marketplace handle revenue share, entitlements, and IP across partners?
- What are the rollback and incident response procedures for model failures?
What leaders are saying
"We've all read reports of poor return on enterprise AI investments in so-called developed markets. Too many projects are failing due to poor implementation, lack of governance or overreliance on a single model or vendor. Through Business AI, we have the opportunity to avoid these failures through the unique framework - to leapfrog what hasn't worked elsewhere and take a more collaborative, independent approach to AI adoption. With Beyond Now's Digital Marketplace, we're able to create a truly agnostic and independent AI ecosystem to build trusted, enterprise-grade AI tools and avoid vendor lock-in." - Rudi Dreyer, CEO, Business AI
"Enterprise AI should deliver real business outcomes - not just experiments. Through Business AI, Mustek is helping our customers move from proof-of-concept to scalable, results-driven implementations. Partnering with Beyond Now accelerates this mission by providing a flexible, vendor-agnostic platform to deploy proven AI solutions at scale." - Hein Engelbrecht, CEO, Mustek
"Business AI is pioneering a model for responsible AI adoption that empowers customers and partners alike. By choosing our digital marketplace, Business AI is creating a vibrant ecosystem where innovation thrives, trust is preserved, and businesses can invest and grow confidently in the age of AI, and we can offer Beyond Now Customer access to proven AI framework for implantation and proven AI use cases." - Angus Ward, CEO, Beyond Now
Bottom line for South African enterprises
Vendor choice, repeatable patterns, and governance are the difference between stalled pilots and production wins. With support from major local enterprises and a platform built for co-development, this partnership gives IT and engineering teams a practical way to ship AI that holds up under security, compliance, and cost scrutiny.
Skills and enablement
If your team needs to level up in model evaluation, prompt testing, or production AI, explore role-based programs here: AI courses by job. For developers moving into applied AI and automation, see this certification path: AI Certification for Coding.
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