SaaS & B2B AI solutions.

SaaS AI solutions: copilots, agents and RAG search built into your B2B product. Underneath: the multi-tenant, billing and enterprise foundations that take a SaaS platform from a handful of accounts to thousands.

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What makes SaaS AI hard.

The SaaS AI challenges we design for before any code is written, so the AI holds up with real users, real data and real auditors.

Tenant-safe AI

Retrieval, prompts and row-level security scoped per tenant, so one customer's data never shows up in another's answer.

Cost per request

Metering, caching and model routing keep AI margins healthy, with usage billing and proration that finance can trust.

Enterprise readiness

SSO, audit logs, role-based access and clear AI data-handling answers for the security questionnaires that unlock bigger deals.

SaaS AI solutions we build

The AI use cases we build for SaaS teams, and the software platforms they run on. Each starts from a measurable goal, passes an eval gate before launch and reaches users through a gradual rollout.

The model work comes from our LLM and AI agent development team, tested by QA and AI evaluation. For results in production, browse our AI case studies.

Compliance we plan for

SOC 2 Type II
ISO 27001
GDPR

✓In-product AI copilots and agents
✓RAG search over customer data
✓Multi-tenant application architecture
✓Usage-based billing and entitlements
✓SSO, SCIM and role-based access
✓Observability, SLO and LLM cost dashboards

SaaS software, shipped.

A recent SaaS engagement and the numbers the client measured. Names withheld where clients asked us to.

Multi-tenant migration

Single-tenant to multi-tenant without downtime, 47 customers migrated over 6 weeks. Infra costs down 64%. Customer SLA breach count: zero.

Browse AI case studies

SaaS AI development services.

The WAMO Labs services most SaaS AI engagements draw on, from LLM integration to the platform around it.

AI integration

Our AI integration services put LLM applications, AI agents and RAG systems into the products and workflows you already run. Measured by evals, guarded in production, with a cost per request you can predict.

Cloud architecture

Cloud architecture and DevOps that keep AI products fast, secure and affordable. MLOps pipelines, GPU inference and LLMOps on AWS, GCP or Azure, with costs you can forecast.

Quality engineering

QA and software testing for business-critical apps: automated tests, performance and reliability work, plus evals and red-teaming that prove your AI features are accurate and safe before users see them.

Questions about SaaS AI projects.

Timelines, cost drivers and compliance, answered plainly. More on how we build and evaluate AI in our AI engineering insights.

Which SaaS AI use cases do you build?

SaaS AI projects we build include in-product AI copilots and agents; RAG search over customer data; and multi-tenant application architecture. Each one ships with a versioned eval set, guardrails and a gradual rollout, on the platform work listed above.

How long do SaaS AI projects take?

Most engagements start with a four-week immersion. By week 3 a first slice is live behind a feature flag for a small share of users, evaluated and instrumented. By week 4 you have a quarter-by-quarter roadmap with named owners. Full timelines depend on scope, integrations and compliance review.

What drives the cost of SaaS AI solutions?

Four things: the systems we integrate with (your product database, billing and identity provider), the compliance scope (SOC 2 Type II, ISO 27001 and GDPR), how much evaluation and human review the use case needs, and inference volume, because cost per request compounds with usage. We size all four during the four-week immersion, so you know what it costs to keep going before you commit to a roadmap.

How do you handle compliance and data privacy in SaaS AI?

We plan for SOC 2 Type II, ISO 27001 and GDPR from the first sprint and decide which data may ever reach a model provider before anything is built. Every AI feature ships with access controls, an audit trail and human review wherever a wrong answer carries real risk.

Building AI in SaaS & B2B?

Tell us the AI use case or product you're working on. We respond within one business day, with a real human and a real opinion.

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