What pushes teams to consider an alternative to Slalom
Honest reasons teams shopping in this category move on. None of these mean Slalom does bad work, just that the fit is wrong for the project.
Your project is AI delivery, not enterprise transformation
Slalom is calibrated for multi-phase enterprise programmes that include strategy, change management, training, and platform implementation. That is the right shape for organisational transformation. For a focused AI product or workflow, the consulting overhead, governance layers, and stakeholder cadence designed for transformation work tend to slow it down.
You want vendor-neutral architecture decisions
Slalom's AI work is closely tied to AWS, Azure, Google Cloud, and Salesforce partnerships. Deep platform expertise is a real strength if you are committed to a stack. The trade-off is that partner-aligned consultancies tend to recommend platform-native solutions even when better alternatives exist for AI specifically.
You want delivery proof, not brand reassurance
Enterprise consulting brings credibility with procurement and the board. Real value. For an AI build, what your engineering lead and CFO want to see is the eval harness, the deployment runbook, the monitoring approach, and the production-grade artifacts that prove this thing will work and keep working.
You want a small dedicated team, not a layered engagement
Enterprise consulting models put strategists, architects, designers, and engineers in different roles with handoffs between phases. That works at scale. For a focused AI product, a small senior team that owns end-to-end is faster and produces less drift between what was scoped and what ships.
How Clarvia approaches AI product delivery
Not presented as universally better than Slalom. The comparison focuses on delivery shape, named artifacts, operating controls, and the evidence a buyer should verify.
Built around bounded AI outcomes
Discovery, build, and rollout are scoped around named artifacts, evaluation criteria, and release gates. The schedule is confirmed after data, integrations, risk, and review requirements are understood.
Vendor-neutral by design
No cloud partnership quotas. We choose the model, provider, and architecture that fit your product, not what satisfies a partner relationship. If AWS Bedrock fits, we use it. If a self-hosted open model on a different stack fits, we use that instead.
AI-first, not AI-as-a-service-line
AI delivery is the focus. The engagement scope defines the evaluation, monitoring, fallback behaviour, prompt or retrieval architecture, and deployment artifacts required by the system risk.
Senior-led, transparent partnership
A small senior team owns delivery. Weekly demos, a shared backlog, acceptance criteria written down before the work starts. You always know where we are and what is shipping next.
Clarvia vs Slalom, category by category
Each row states both positions and then what it implies, including the cases where Slalom is the better answer.
AI consultancy with the factory already built. We ship working AI systems with small, focused teams. Working software, not a discovery deck.
Management and technology consultancy offering enterprise transformation, data, cloud, platform, and AI services, including work delivered with major technology partners.
Core Offering
AI product development. We build the actual software. From data pipelines to ML models to user-facing applications, we ship working AI products, not recommendations about what to build.
Management and technology consulting. Slalom advises on strategy, runs change management, implements cloud platforms, and builds enterprise applications. Their AI services focus on enterprise analytics, data strategy, and cloud-based ML deployments.
AI Approach
Custom AI products built for your specific problem. We select the right models, architecture, and approach based on what your product needs, not based on which cloud vendor we have a partnership with.
Cloud-partner-aligned AI solutions. Slalom's AI work is closely tied to AWS, Azure, and Google Cloud platforms. This means deep implementation expertise with cloud-native ML services, which is a strong advantage if you are committed to a specific platform.
Engagement Structure
Lean, focused product teams. You work directly with senior engineers and product thinkers. Every person on your project is building something.
Large consulting engagement model. Slalom staffs projects with a mix of senior consultants and junior associates. Engagements often include strategy, change management, training, and implementation phases. Each phase adds value but also adds time and cost.
Speed vs Scale
The schedule is set after scope, data, integrations, evaluation, and review gates are understood, with progress assessed against named artifacts.
Enterprise consulting schedules depend on programme breadth, governance, procurement, platform work, and organisational change requirements.
Pricing
Project-based pricing tied to specific deliverables. Transparent, predictable, and directly connected to product outcomes. No surprise bills for "strategy alignment workshops."
Consulting scope may include strategy, platform, change management, and training alongside implementation. Those responsibilities should be separated clearly in the proposal.
When Slalom is still the right choice
You are running an enterprise-wide digital transformation programme and AI is one component of a broader scope
Change management, training, and organisational readiness matter as much as the technology itself
You are deeply invested in AWS, Azure, Google Cloud, or Salesforce and want a certified partner with deep platform expertise
You need a US consultancy with established local presence across many cities
Enterprise governance, executive stakeholder management, and large-team coordination are central to the engagement
Common questions
Are you a smaller version of Slalom?
No. Slalom is a management and technology consultancy with broad practice areas across strategy, cloud, analytics, and delivery. We are a focused AI product development agency. We do not aim to replicate enterprise consulting at smaller scale. Different model, different fit.
Can you handle enterprise procurement and security review?
We can provide the published data-handling, governance, and evaluation information in our Trust Center for review. Whether the engagement satisfies a specific procurement or security process depends on that organisation's requirements and assessment.
What if our AI project really does need change management alongside it?
We will tell you. If your project genuinely requires multi-department change management, training programmes, and organisational readiness alongside the technology, we are the wrong partner and we will say so on the first call. We turn down projects that are not AI-led product delivery, because that is what we are built to do well.
Do you have AWS, Azure, or Google Cloud partnerships?
We work across all major clouds and pick what fits the project. We deliberately do not anchor to a single partner because AI architecture decisions should be driven by what is best for the product, not by partnership quotas. Model and provider selection for LLM, retrieval, and agent systems is part of our generative AI consulting services. If a specific platform is a hard requirement on your side, we work within it without bias.
Why consider a focused agency instead of a large consultancy?
Company scale and product quality are different questions. Review the proposed team, relevant evidence, evaluation plan, governance, and accountability for the outcome. A focused agency and a large consultancy can both fit, but they solve different organisational needs.
Does Slalom's cloud partnership give them better AI capabilities?
Slalom's partnerships with AWS, Azure, and Google Cloud give them deep knowledge of those platforms' ML services. That is genuinely valuable if you are committed to a specific cloud. The trade-off is that partner-aligned consultancies tend to recommend platform-native solutions even when better alternatives exist. Clarvia evaluates all options and recommends what is best for your product, not what satisfies a partner relationship.
What if I need both strategy and product development?
If you need large-scale enterprise AI strategy involving executive alignment, organisational change, and multi-department rollouts, Slalom is well-suited. If you need a clear AI product strategy followed by rapid building and shipping, Clarvia covers both without the consulting overhead. We do strategy too, but it is product strategy that leads directly to working software.
Can Clarvia work alongside Slalom on a project?
Yes. Some companies use a large consultancy for enterprise strategy and change management while engaging a specialised agency for the actual AI product build. Clarvia can handle the product development workstream while Slalom handles organisational readiness. The two are complementary, not competing.
Build an AI product, not a transformation programme.
Book a free 15-minute call. We will tell you honestly whether your project fits a focused AI delivery model or whether a broader consulting engagement is the right call.