Knowledge base
The public library behind the readiness model.
High-level SaaS CTO guidance for governance, cloud platforms, data protection, production readiness and customer trust. The service applies this knowledge to a real company and turns it into evidence-led decisions.
Reusable guidance
Specific problems companies keep meeting.
The knowledge base stays broad because the review model needs reusable guidance behind it. The page is organised as a reference library, not a sales page or a blog feed.
Set the company up properly
Identity, domains, devices and policies are the controls that stop early speed becoming later drag.
Domain
The company domain is part of the trust boundary. It anchors identity, email, DNS, the corporate website, customer communication and future product endpoints. If domain ownership or DNS control is unclear, the company can inherit avoidable security, operational and recovery risk.
Email is part of the company's external credibility and internal control environment. It is how the company communicates with customers, suppliers, regulators and staff. Weak email authentication increases impersonation risk and makes later security reviews harder than they need to be.
External presence
The corporate website, privacy policy and customer contact channels are part of the operating model. They do not have to live on the final product platform, but the company needs to understand who owns them, who can publish changes and what public commitments are being made.
Tenant security monitoring
The Microsoft tenant is an early control plane. It should be useful on day one, but it should also be monitored because identity compromise quickly becomes business compromise.
Device and endpoint governance
Identity is the root control plane, but the machines people use to access code, Microsoft 365, Azure and customer data become part of the control plane too.
Policies and procedures
Policies describe intent. They say what the company believes, what standard it is trying to meet and what behaviour is expected.
Agentic software delivery governance
Agents used by the delivery team need a different governance model from AI models embedded in the product. Delivery agents may not be part of the customer-facing service, but they can still create risk because they may read code, write code, inspect logs, summarise documents, generate infrastructure changes or draft customer-facing material.
Earn customer trust
The evidence customers ask for starts before sales: data protection, contracts, testing and clear support promises.
Data protection assurance
Data protection should be treated in the same way the product is treated with penetration testing. Before wider customer onboarding, the company should get an external review of its data protection position.
Customer trust pack
The governance work should produce useful client onboarding evidence. This is not compliance for its own sake. It helps sales and onboarding because the company can answer trust questions quickly and consistently.
Contracts and support promises
Commercial promises quickly become operational obligations. A young SaaS company should be careful not to promise enterprise-grade support, availability or recovery before the platform and team can evidence it.
Testing and release quality
Deployment safety depends on more than blue/green infrastructure. The team needs confidence that the thing being deployed is known, tested and reversible.
Make production survivable
Production is a business promise. The architecture, cost model and incident process need to match that promise.
Container platform decisions
Use containers as the default packaging stance. They give the product a flexible route from POC to Pilot to Production without forcing the final hosting decision too early.
Cost governance and unit economics
POC, Pilot and Production are partly cost-control stages. Each step accepts more cost only when the risk, customer expectation or operational promise justifies it.
Incident management
Policies and procedures are only useful if the team can follow them under pressure. Rehearsals turn governance from paperwork into operational muscle memory.
Pilot to Production data migration
Pilot data should not accidentally become Production data. The transition needs an explicit decision.
Design the SaaS operating shape
The product model affects support, billing, supply chain, customer isolation and the promises the business can make.
Multi-tenancy and customer isolation
For SaaS, tenant isolation is both an architecture decision and a governance decision. It affects data models, authorisation, logging, backups, support tooling and customer trust.
Payments and billing
If the SaaS product takes payments, billing becomes part of the data, security and support surface. The simplest early position is to avoid card-data handling wherever possible.
AI model governance
AI models used by the product need their own governance model. They are different from agents used by the delivery team because they sit closer to customer workflows, user data, automatic processing and contractual promises.
Software supply chain
The platform should make it clear what code, packages, images and tools are trusted enough to become part of the product.
Stage gates
Stage gates are decision points. They help a company decide whether it is ready to move to the next level of customer exposure, operational risk and commercial promise. They are not ceremonies and they are not a replacement for judgement.
Advisory themes
What this points towards
The blog is better for opinion, stories and lessons. The knowledge base is better for reusable reference material that supports the LinkedIn campaign and the readiness review model.