AI for SaaS
B2B and B2C SaaS companies adding AI features into their existing product without slowing down the core team.
The pain points SaaS teams keep hitting
- AI features ship as one-off prompts that don't scale or hold a quality bar
- Cost-per-user creeps when LLM calls aren't budgeted
- Search and recommendation features still use 2018-era keyword matching
Where AI moves the needle in SaaS
- RAG-powered docs/help search. Reduces support ticket volume 20–40%
- Onboarding copilot. Lifts week-1 activation 10–25%
- Auto-tagging / classification. Eliminates a manual ops task entirely
- AI-drafted reports / summaries. Saves 5–15 hours per power-user per month
Example use cases we've shipped
- RAG over your docs + tickets to power an in-product help agent
- LLM-graded onboarding evals to detect users about to churn
- Streaming chat UX with proper retry/cancel/abort semantics
- Per-tenant cost guardrails so a single power user can't blow your bill
Compliance & risk notes
SOC 2 Type II readiness, per-tenant data isolation, and PII redaction at the prompt layer are table stakes for any SaaS over ~$1M ARR.
SaaS case studies
- AgentFlow - Visual AI Agent Builder — A no-code platform for building AI-powered automation agents through an intuitive drag-and-drop canvas interface.
- AI Walay - WhatsApp Business Campaign Manager — A multi-tenant SaaS platform enabling businesses to manage WhatsApp marketing campaigns, contacts, and customer conversations through the WhatsApp Business Cloud API.
- ProLeads — AI-powered B2B lead generation platform that helps sales teams find verified decision-makers using natural language search queries.
- AgenticAI - AI-Powered CV Screening Platform — An intelligent recruitment platform that uses AI to analyze and rank CVs against job requirements, helping companies find perfect candidates in minutes instead of weeks.
Common questions from SaaS teams
- Do you work inside our existing repo?
- Yes — we follow your branch protection, code review, and deploy process. We don't push to main without review.
- How do you keep the per-tenant cost predictable?
- Hard budget per tenant in the SDK wrapper, model-tier routing (cheaper for cheap calls), and aggressive caching of retrieval results. You see the dashboard from day one.
- Can you ship without disrupting our weekly release cadence?
- Yes — we work on a long-lived feature branch behind a flag, demo weekly, and merge in pieces.