Forward-deployed AI engineering for serious internal work
We build the AI systems your company would build if it had the team in-house.
Rowbase embeds with teams to map messy workflows, build a client-owned context layer, and ship practical AI tools directly inside the environment where the work already happens.
Built by founders & engineers from
How we work
Less pilot. More production.
Most AI pilots stall because they start with the model. We start with the workflow: what decision is being made, what context is missing, who needs to approve it, and where the result has to land.
.01
Start with the workflow
We map the decisions, approvals, source material, edge cases, and handoffs that already define how the work gets done.
.02
Build the context layer
We connect the right documents, systems, decisions, and operating history into a client-owned layer with provenance, permissions, and review built in.
.03
Ship production AI
We build the applications, agents, and automations inside your environment, then tighten them against real usage until they are useful enough to keep.
01
Weeks
from kickoff to a useful first version — not quarters
02
3–5×
typical throughput lift on the workflows we ship
03
100%
of agent answers grounded in cited source material
04
Yours
the code, the context layer, the operating leverage
Rowbase POV
Most software was built for human coordination. The next generation will be built for grounded, source-aware execution — the kind a serious team will actually let into their workflow.
What we do
Senior builders for the ambiguous middle.
Rowbase is for companies that know AI should matter, but whose workflows are too specific, messy, or sensitive for off-the-shelf tools. We combine AI, data, and software engineering in one engagement so the work can move from idea to production.
01
AI workflow implementation
Turn manual, high-value processes into AI-assisted systems with clear review loops, audit trails, and measurable business outcomes.
02
Company context layer
Give your team a durable knowledge base that connects docs, tools, decisions, and operating history without handing ownership to a vendor.
03
Data and AI engineering
Build the ingestion, retrieval, evaluation, permissions, and observability needed for AI systems people can trust in daily work.
04
Internal AI products
Create custom tools, agents, and copilots that fit your existing systems instead of forcing the business around a generic product.
Where it fits
For high-context work trapped in people, files, and process.
Rowbase is a fit when the answer needs to come with sources, the workflow crosses several systems, and someone still needs to review the output before the business acts on it.
Production AI workflows
Client-owned context layers
Source-grounded Q&A and agents
Embedded AI engineering
Human review and approval flows
Permission-aware internal tools
Agent archetypes
What we actually build.
Three patterns cover most of what we ship. Every engagement is specific to the workflow, but the underlying shape is usually one of these.
.01 · Knowledge
Source-grounded Q&A agents
Answers questions across docs, policies, contracts, and prior decisions — with citations to the exact paragraph the answer came from.
- Plain-English answers with line-level source citations
- Permission-aware retrieval that respects existing access rules
- Confidence gating so low-certainty answers route to a human
- Feedback loop that captures every correction
.02 · Workflow
Workflow & approval agents
Drafts the document, runs the review, or routes the approval — embedded in the system where the work already happens, with humans in the loop on anything material.
- First-pass drafts in your firm's voice and structure
- Configurable review surfaces for novel or high-stakes decisions
- Audit trail of every change, every reviewer, every source
- Integrates into existing deal, claims, or proposal workflows
.03 · Copilot
Embedded internal copilots
A teammate for non-technical operators — sitting inside the tools they already use, grounded in your operating history, never a generic chatbot.
- Suggested responses, never auto-sent without review
- Grounded in your wiki, tickets, changelogs, and tribal knowledge
- Confidence-aware routing to senior teammates when needed
- Improves with every edit a teammate makes to its suggestions
What it looks like in production
The system you can actually watch get better.
Ready when you are
Have a workflow AI should already be helping with?
FAQs
Have a workflow AI should already be helping with?
Send us the workflow, the systems involved, and what a useful first version would need to answer or do.