80+
B2B SaaS products we've worked on
Trusted by 80+ SaaS companies
Add AI features that ship to production
Senior strategy on what's worth building. Managed agents ship it as reviewed PRs.
Trusted by 80+ SaaS companies
Hype-driven feature lists with no clear user job.
Months of build, low adoption, wasted budget.
ML hires take 6+ months and lock in fixed cost.
Window closes before the team is ready.
Demos work, production breaks on real data.
Trust drops on day one. Hard to recover.
Cost runs away with token usage and bad architecture.
Margins crater quietly until the bill arrives.
Senior product thinking on what's worth building, scoped to a measurable outcome.
Managed AI agents and senior developers ship the implementation, with cost and quality guardrails.
80+
B2B SaaS products we've worked on
10+
years building B2B SaaS products
4.9
stars on Clutch
From single-feature additions to agentic workflows.
In-product chat, drafting, and recommendations grounded in your data.
Search your documents, tickets, or product data with relevance that beats keyword.
Multi-step actions where the AI plans, calls tools, and reports back. With proper guardrails.
Categorization, summarization, extraction, and triage. Quiet wins, real time saved.
...and not generic product design agencies or freelancers
10+ years building products. 80+ SaaS companies. 15+ products launched. We know what works.
We focus on B2B SaaS and PLG. Complex flows, product analytics, feature adoption. This is our daily work.
Pretty screens don't matter if they don't solve problems. Like a PM, we balance desirability, feasibility, and viability.
We've worked with companies from first customers to rapid growth. Our decisions are backed by what we learned on those projects.
From feature audit to production, with cost and quality guardrails baked in.
Senior humans audit your product and propose AI features tied to a real user job and a measurable outcome. No hype-driven lists.
Model choice, retrieval strategy, evals, cost ceilings, and fallback behaviour. Specced before any code is written.
Managed agents implement. Senior developers review prompts, retrieval, evals, and integration with your data and auth.
Live preview wired to a sample of your real data. You exercise it, we tune. Approve, we merge.
Cost, latency, and quality dashboards from day one. We iterate on regressions surfaced by evals or users.
AI features that hold up in production, with cost and quality guardrails baked in.
Magic Team Magic Team is a managed team of AI agents and senior humans that ships real code. We deliver AI features as reviewed PRs into your repo, with cost and quality guardrails built in. Pay only for code that ships.
The first step is a quick chat.
