From a 20-person clinic to a national bank, Rowth.ai brings senior practitioners who take you from AI experiments to production — and we build on top of the systems you already run. No rip-and-replace.
Most enterprise AI dies between the prototype and production — at integration, governance, or change management. We own the whole path, not just the fun part.
You've invested years in your data, your apps and your cloud. Rowth adds an intelligence layer that plugs into all of it — so you get production AI without re-platforming anything.
Every size, every industry, every level of AI maturity. We meet you where you are and build from there.
A focused 60-day audit and one high-ROI use case. We prove value on top of your current tools before you commit to anything bigger.
You have promising prototypes that never shipped. We take the best one to production — with MLOps, governance and a clean handoff.
Multiple use cases, multiple teams. We stand up an AI platform and COE so the whole organisation can ship on shared, governed rails.
From the strategy that precedes any code to the plumbing that keeps it running, one accountable team owns the outcome.
Custom LLMs, retrieval with citations, and agents that take action — tuned to your domain, with deployable guardrails.
High throughput, low latency, continuous training, drift detection and automated rollback — the unglamorous parts done right.
Business data, chat sessions, documents — unified.
Everything executes at once, so the system stays fast under load.
We assemble strategy, models and operations into one reliable engagement, layered onto your existing stack.
Across the dimensions that decide whether AI actually ships, Rowth's embedded-pod model beats both a from-scratch in-house build and a generic consultancy.
| Dimension | Rowth.ai | In-house build | Generic vendor |
|---|---|---|---|
| Time to first production model | 6 weeks | 7 months | 4 months |
| Senior practitioner ratio | 80% | 20% | 35% |
| MLOps & monitoring included | Always | Rarely | Add-on |
| Works on your existing stack | Always | Varies | Rip & replace |
| Responsible-AI framework | Built in | DIY | Optional |
| Knowledge handed to your team | Always | N/A | Limited |
The value of AI is domain-specific. Pick an industry to see what changes when Rowth owns the engagement.
A real-time fraud engine scoring 7M transactions a day at sub-200ms — retrained weekly, with an analyst console and automated rollback.
Nightly batch jobs catch fraud hours late, and a brittle rules engine floods analysts with false positives.
Start with an honest audit. Scale to embedded pods. No lock-in, no surprise SOWs.
No. Rowth is deliberately additive — we build an intelligence layer on top of the data, apps and cloud you already run, and integrate with them. No rip-and-replace, no re-platforming.
Every size. We've taken 20-person teams from zero AI to a first production use case, and stood up AI platforms for national enterprises. The engagement model scales to fit you.
Yes. Every engagement is built around your data, your stack, your KPIs and your regulatory environment. We assemble the pod and the scope to fit — there is no off-the-shelf package.
No. We handle strategy, build, deployment and ongoing operations — and always enable your team with documentation and runbooks so you own what we build.
An audit takes about 60 days. A scoped sprint produces a working proof of concept in roughly 8 weeks. Embedded pods typically have a first model in production by week six.
We don't disappear at go-live. Engagements include monitoring, drift detection, retraining and on-call support, with a clean handoff to your team whenever you're ready.
A senior practitioner reads every brief and responds within 48 hours — with a sharp first read, not a templated proposal.