We review your existing SaaS architecture, design the target state, and produce a prioritised roadmap — whether you are scaling past your current limits, preparing for investment, or planning a major platform refactor.
SaaS Architecture Patterns and Technologies We Design and Review
Architecture decisions made in the first six months of a SaaS product's life are often still bearing weight — and cost — three years later. The data model chosen before product-market fit was found. The service boundaries drawn before the team understood the business domain. The infrastructure choices made when scale was theoretical. Architecture consulting exists to make those decisions deliberately, with the benefit of experience across many similar platforms.
A architecture review engagement does not prescribe a complete rebuild. It identifies the specific decisions that are generating the most cost — slow deployments, poor query performance, brittle integrations, scaling bottlenecks — and prioritises the interventions that deliver the highest return. Most platforms have three to five architectural improvements that would account for eighty percent of the operational improvement, and architecture consulting finds them.
For teams building a new platform, architecture consulting compresses the learning curve of building the first version wrong and refactoring it. A four-week architecture design engagement that produces a clear data model, service decomposition, and API contract typically saves months of expensive rework later.
Architecture decisions made by individual developers at implementation time — no documented rationale
Architecture documented before implementation — diagrams, trade-off records, and decision logs
Scaling bottlenecks discovered in production under customer load
Bottlenecks identified and addressed in design, not in a production incident at 2am
Technology choices made by familiarity rather than fitness for purpose
Technology advisory based on your access patterns, team size, and compliance requirements
No documented data model — tribal knowledge, no onboarding path for new engineers
Data model documented and reviewed — every table, relationship, and index decision recorded
Refactoring decisions deferred until the cost of the current approach exceeds the cost of change
Improvement roadmap prioritised by business impact — highest-return changes shipped first
The cost of poor architectural decisions compounds. A data model that does not support multi-tenancy requires a full migration. A monolith that cannot be independently deployed blocks team velocity at 20 engineers. Architecture consulting front-loads that cost at the lowest possible point in the product lifecycle.
Seven specialist service lines, each built for a specific type of architecture challenge.
We document your current architecture — data model, service boundaries, API design, and infrastructure — and identify the specific risks, bottlenecks, and design gaps that are limiting performance, velocity, or reliability. Delivered as a written report with a prioritised improvement roadmap.
For new platform builds, we design the target architecture before implementation begins: data model, service decomposition, API contract design, infrastructure blueprint, and technology stack recommendation. Your engineering team implements against a clear, reviewed design.
We design the decomposition path from monolith to microservices, identifying the service boundaries, data ownership rules, and migration sequence that minimise risk. We apply the Strangler Fig pattern and domain-driven design principles to produce a realistic, phased migration plan.
We review your data model, query patterns, and indexing strategy, and recommend optimisations at every layer: query tuning, index design, read replica introduction, caching with Redis, CQRS read model separation, and horizontal partitioning for high-volume tables.
We design event-driven architectures using Kafka, RabbitMQ, or AWS EventBridge — defining the event schema, producer/consumer contracts, error handling strategy, and dead-letter queue design. We identify which workflows benefit from async event processing and which require synchronous responses.
We review the authentication and authorisation model, data encryption at rest and in transit, API security controls, secrets management, and network segmentation. We identify gaps against OWASP and your compliance framework and produce a remediation roadmap with implementation guidance.
We provide vendor-neutral technology advisory — evaluating database choices, messaging systems, cloud providers, and framework selections against your specific requirements. We produce written trade-off analysis so your team understands why a recommendation was made, not just what it was.
A structured six-stage process from free scoping call to live implementation support and ongoing advisory.
We discuss your platform, team, scale requirements, and the specific challenges driving the engagement. We agree the scope of the review or design work, the deliverable format, and the timeline. This session is free.
We review your codebase structure, data model, API design, infrastructure configuration, and operational metrics. For greenfield engagements we review your product requirements, team structure, and existing system integrations.
We produce the target architecture: diagrams, data model documentation, service boundary definitions, API contract sketches, and infrastructure blueprints. We hold working sessions with your team to review and refine the design.
We produce a prioritised improvement roadmap — for existing platforms — or an implementation sequence — for greenfield design. Each initiative is described with the business impact, technical approach, estimated effort, and dependencies.
We support your engineering team through the implementation of the architectural changes, reviewing pull requests, answering design questions, and adapting the plan as implementation surfaces new constraints. This phase is scoped separately from the design engagement.
For teams that want continuous architecture input, we offer a monthly advisory retainer covering structured design review sessions, code review for architectural decisions, and on-demand consultation on specific design questions as they arise in your product development.
We discuss your platform, team, scale requirements, and the specific challenges driving the engagement. We agree the scope of the review or design work, the deliverable format, and the timeline. This session is free.
We review your codebase structure, data model, API design, infrastructure configuration, and operational metrics. For greenfield engagements we review your product requirements, team structure, and existing system integrations.
We produce the target architecture: diagrams, data model documentation, service boundary definitions, API contract sketches, and infrastructure blueprints. We hold working sessions with your team to review and refine the design.
We produce a prioritised improvement roadmap — for existing platforms — or an implementation sequence — for greenfield design. Each initiative is described with the business impact, technical approach, estimated effort, and dependencies.
We support your engineering team through the implementation of the architectural changes, reviewing pull requests, answering design questions, and adapting the plan as implementation surfaces new constraints. This phase is scoped separately from the design engagement.
For teams that want continuous architecture input, we offer a monthly advisory retainer covering structured design review sessions, code review for architectural decisions, and on-demand consultation on specific design questions as they arise in your product development.
Select a sector to see how we approach architecture consulting for your industry's specific constraints and scale requirements.
Financial services SaaS teams face architecture challenges unique to the sector: event-sourced ledger design, regulatory audit trail requirements, real-time processing under load, and strict data residency constraints.
Financial services SaaS teams face architecture challenges unique to the sector: event-sourced ledger design, regulatory audit trail requirements, real-time processing under load, and strict data residency constraints.
Healthcare SaaS architectures must balance HIPAA compliance, integration with legacy clinical systems, and the operational demands of high-availability medical software.
E-commerce platforms face architecture challenges at scale: catalogue complexity, high-concurrency checkout, search relevance, and integration with dozens of fulfilment and payment partners.
HR platforms serve complex organisational hierarchies across multiple countries and jurisdictions, requiring careful permission modelling, multi-tenancy design, and integration with payroll and identity systems.
Logistics platforms must handle real-time data ingestion from IoT devices and carrier systems, event-driven order state machines, and geographic search and routing at scale.
Media and publishing SaaS platforms require content delivery architecture, subscription and entitlement systems, and recommendation engines that personalise at scale.
Perimattic's work resulted in stable production systems. The team was helpful, easily accessible, and communicative through email. Their professionalism was impressive.
Quality
4.5
Schedule
5.0
Cost
5.0
Willing to Refer
4.5
DevOps Managed Services · Oct 2023 – Aug 2024
24/7 monitoring and support for production environments plus Linux server administration for a leasing automation company.
The new architecture is scalable and highly efficient, saving a lot of money in fees. Perimattic provides high-quality IT consulting and cloud development work promptly and at great value. The team remains involved from the planning stage to providing support, showing diligence and proactiveness.
Quality
5.0
Schedule
5.0
Cost
4.5
Willing to Refer
5.0
AWS Migration (Legacy → Microservices) · Nov 2018 – Ongoing
Transitioned a travel systems company's legacy server system to an AWS-based microservices architecture with ongoing maintenance.
Four structural advantages that separate experienced architecture consulting from generic technology advice.
We do not have commercial relationships with cloud providers, database vendors, or framework maintainers. Our recommendations are based on fitness for your specific requirements — access patterns, team size, compliance constraints, and budget — not on familiarity or incentive.
Every architecture pattern we recommend has been tested in production in our delivery projects — not just described in theory. We know where microservices boundaries create operational pain, where event sourcing becomes operationally complex, and where caching introduces consistency bugs.
Architecture consulting is only valuable if the knowledge is captured. Every engagement produces written deliverables — diagrams, trade-off records, and decision logs — that your team owns. We do not deliver architecture as a verbal debrief that evaporates after the engagement ends.
Architecture consulting is most valuable as a continuing relationship rather than a one-off engagement. We offer monthly advisory retainers so your team has access to experienced architecture input throughout the product development lifecycle, not just at the moments of crisis.
“Unlike boutique dev shops that build to spec without strategic context, or large consultancies that advise without shipping, Perimattic brings both capabilities to every engagement.”
SaaS architecture consulting is a structured engagement in which experienced software architects review your existing or planned platform architecture, identify risks and bottlenecks, and design improvements that align the technology with your product and business requirements. It covers the full technology stack: data models, API design, service decomposition, infrastructure, security, and operational processes. Unlike general development work, architecture consulting produces a documented design that your engineering team can implement, rather than implementation code itself.
Architecture consulting is most valuable at three moments: before building, when you are designing a new platform and want to avoid the technical debt of ad-hoc decisions; at a growth inflection point, when performance problems or operational complexity suggest the current architecture is not scaling; and before a major investment round, when technical due diligence requires an independent assessment of the technology foundation. It is also valuable when a team is planning a significant architectural shift — moving from a monolith to microservices, or from on-premise to cloud — and wants to reduce the risk of the transition.
A Perimattic architecture review covers: current state documentation of the system architecture, data model, and infrastructure; risk identification covering performance bottlenecks, single points of failure, security weaknesses, and scalability limits; a gap analysis against industry best practice for platforms of your type and scale; and a prioritised improvement roadmap with clear trade-off analysis for each recommendation. The review is delivered as a written report with diagrams, not just a verbal debrief.
A monolith is a single deployable application that contains all of the platform's functionality — simpler to develop and operate at low scale but increasingly difficult to change, test, and deploy independently as the codebase grows. Microservices decompose the platform into independently deployable services, each responsible for a specific business capability — enabling independent scaling, independent deployment, and polyglot technology choices, but introducing distributed systems complexity around service communication, data consistency, and observability. We recommend microservices when the independent deployment and scaling benefits clearly outweigh the operational overhead — typically when teams are large enough that deployment coupling creates release bottlenecks.
Event-driven architecture (EDA) is a pattern where services communicate by publishing and consuming events via a message broker — Kafka, RabbitMQ, or AWS EventBridge — rather than making synchronous API calls. EDA is the right choice for workflows where services must react to state changes in other services without tight coupling: order processing pipelines, notification systems, audit trails, and data synchronisation between systems. It is not the right choice for simple CRUD operations or flows where the caller needs an immediate, synchronous response.
Database scaling strategy depends on the access patterns, data volume, and consistency requirements of the platform. We typically start with query optimisation and indexing, then introduce read replicas for read-heavy workloads, then introduce caching layers with Redis for frequently accessed data. If query patterns allow it, we recommend CQRS — separate read and write models — which decouples the scaling of the query layer from the write layer. Horizontal sharding or partitioning is introduced when single-instance vertical scaling approaches its practical limit.
CQRS — Command Query Responsibility Segregation — is an architectural pattern that separates the data model used for write operations (commands) from the data model used for read operations (queries). Commands update the authoritative write store; query handlers build and serve optimised read models — often denormalised for specific reporting or API use cases. CQRS is valuable when read and write load characteristics differ significantly, when query performance is bottlenecked by complex joins on the write model, or when you need multiple read projections from the same underlying data. It adds architectural complexity and is not the right choice for simple platforms.
An architecture review of an existing platform takes one to three weeks depending on the scope and complexity of the system. A greenfield architecture design engagement — producing the data model, service decomposition, API design, and infrastructure blueprint for a new platform — typically takes three to six weeks. An ongoing architecture advisory retainer runs month-to-month, with structured review sessions and on-demand input on specific design decisions as they arise.
An architecture review starts from USD 8,000 for a focused scope, and from USD 15,000 for a comprehensive review covering the full stack. A greenfield architecture design engagement typically ranges from USD 15,000 to USD 40,000 depending on the complexity of the platform being designed. Ongoing advisory retainers start from USD 3,000 per month. We scope every engagement before quoting and provide a clear view of what is covered.
A typical architecture review produces: a current-state architecture diagram with risk annotations; a prioritised improvement roadmap with trade-off analysis; recommendations for quick wins versus longer-term restructuring; and a technology stack advisory covering the specific tools and frameworks we recommend for your use case. For greenfield design engagements, deliverables include data model diagrams, service decomposition diagrams, API contract design, and infrastructure architecture blueprints. All deliverables are written documents your team owns outright.
Whether you need a review of your current platform or a clean architecture for a new one, we start with a free discovery call to understand your constraints and define the scope. No generic recommendations — every engagement is specific to your platform.