B2B SaaS & professional services

B2B products fail in the second hundred customers, not the first ten: single-tenant code that will not scale, billing, roles and permissions rebuilt on every project, knowledge locked in documents and inboxes, and senior people doing repetitive back-office work. The market keeps rewarding those who get it right: Gartner (2024) forecast worldwide end-user spending on public cloud services at around $675 billion in 2024, with SaaS the largest segment. Buyers now expect enterprise controls from day one: SSO, audit logs, data-processing terms under GDPR Article 28, and often a SOC 2 or ISO 27001 posture.

• Single-tenant code that cannot scale to the next hundred clients
• Billing, roles and permissions rebuilt on every project
• Knowledge locked in documents and inboxes
• Repetitive back-office work eating senior time

We build multi-tenant SaaS platforms with billing, roles and public APIs, client portals and self-service, internal tools with workflow and approvals, and we extend product teams for a roadmap they cannot staff alone. Tenancy, RBAC, audit logging and metering are designed once and reused; authentication follows NIST SP 800-63 (NIST, 2017, revision 4 in progress) for password, MFA and session rules. The stack is Python (FastAPI, Django) or PHP (Laravel, Symfony) with Vue or React, PostgreSQL and queues, the same combination that Stack Overflow’s Developer Survey (2024) shows among the most widely used web technologies.

• Multi-tenant SaaS platforms with billing, roles and public APIs
• Client portals and self-service
• Internal tools, workflow and approval systems
• Team extension for your product roadmap

AI moves B2B numbers where knowledge work is repetitive: answering questions over documents, tickets and CRM, drafting and reviewing documents with human sign-off, classifying and routing requests, and predicting churn from usage. McKinsey (2023) estimated that generative AI could add $2.6–4.4 trillion annually across use cases, with customer operations, marketing and sales, software engineering and R&D capturing most of it. We build these as RAG assistants grounded in your data with citations, not as free-running chatbots, and follow the OWASP Top 10 for LLM Applications (2025) for prompt injection and data-leakage controls. See AI & machine learning.

• Knowledge assistants over documents, tickets and CRM
• Document drafting and review with human sign-off
• Classification and routing of requests
• Usage analytics and churn prediction

Because most of our 500+ projects were B2B products, and we know what the second hundred clients will break: tenant isolation, billing edge cases, permission matrices and reporting queries. We design for them in the first sprint. Security is built in against the OWASP Application Security Verification Standard (ASVS 5.0, 2025) and verified under security services, so enterprise questionnaires get answers rather than promises. Engagement models range from fixed-scope MVP to a dedicated team; see how we work.