Industries / B2B SaaS
Automate your go-to-market ops, or ship AI inside the product.
SaaS teams usually want two things from AI: fewer manual steps across sales, onboarding and support, and AI features customers will pay for. We do both, with the same discipline: clear success measures, evaluations before launch and monitoring after it.
Fit
Who this is for
- Seed to growth-stage SaaS companies with a product in market.
- Revenue, customer success or support leaders with a backlog of manual workflows.
- Product teams that want to ship an AI feature without pausing the roadmap.
Use cases
Workflows we can automate
- Lead research and CRM hygiene. Enrich new sign-ups and leads, score them against your ideal customer profile, write a research note for sales and keep CRM fields consistent.
- Onboarding and activation nudges. Watch product events, spot accounts that stall during setup and trigger the right help: a tailored email, an in-app message or a task for customer success.
- Support deflection grounded in your docs. Answer product questions from your documentation and past resolved tickets, cite the source, and hand off to a person when confidence is low.
- Churn and expansion signals. Combine usage, billing and support data into weekly account summaries that flag risk and expansion opportunities for the account owner.
- In-product AI features. Design and build features such as summaries, assistants, smart search or agent workflows inside your product, with cost controls and evaluations.
Which package fits
Where to start
- Automation & Agent Build, from $12,000. For internal workflows across sales, success and support: one automation, live in weeks.
- AI Product Engineering, from $30,000. For AI features inside your product, with design, evaluations, rollout and handover to your engineers.
- Automation Operations, from $3,000/month. When several automations or AI features need monitoring, prompt and model updates and steady improvement.
Guardrails
How we keep it safe
- Customer data stays within the systems and AI providers you approve, and access follows least privilege.
- AI features ship with evaluations, usage limits and logging so quality and cost are visible.
- Your engineers get documented code in your repositories; nothing is locked to us.
Estimate
Check the numbers first
Use the ROI calculator to estimate hours saved and payback for your team, or grab the AI Automation Readiness Checklist to see whether a workflow is ready to automate.
Explore
Related services
FAQ
Questions we hear from b2b saas teams.
Can you work with our engineering team?
Yes. We work in your repositories and review process, and we plan the handover from day one so your team can own the feature after launch.
How do you keep AI feature costs under control?
We choose models per task, cache where it is safe, set usage limits and track cost per request from the first release, so pricing decisions rest on real numbers.
Should we build an AI feature or buy a tool?
Buy when a tool solves the problem and it is not a differentiator. Build when the feature is part of what customers pay you for, or when it depends on your own data and workflow.
Which models do you use?
We are not tied to one provider. We pick models for each task based on quality, latency, cost and your data requirements, and we design so the model can be swapped later.
Get started
Tell us about the workflow.
A free 30-minute call is enough to tell whether it is worth automating, which package fits and what it would cost.