AI automation uses LLMs such as OpenAI and Claude, orchestrated by tools like n8n, to take over repetitive information work: data entry, reconciliation, triage, and drafting. CapregSoft builds these workflows with RAG over your own documents and a human-in-the-loop threshold, typically automating 70–90% of the targeted manual work with payback in 2–3 months.
Manual work is invisible until you add it up. A few minutes here, a recurring report there, an inbox someone triages by hand, and suddenly a third of your team's week is gone to work no human should be doing.
We're an AI automation agency that builds systems, not demos. We wire your tools together with n8n, add LLM reasoning with LangChain and OpenAI or Claude, and ground answers in your own data using RAG and vector databases. The result: workflows that run themselves and free your team for work that actually needs a human.
We start where the payback is fastest. Most automations we ship recover their cost in 2–3 months by removing 70–90% of a repetitive workflow, and they keep running long after the invoice is paid.
What you actually get.
Of a manual workflow removed, so your team stops doing work an agent can do.
Typical payback period before the automation is saving more than it cost.
RAG over your own data means the AI cites your facts, not hallucinations.
How we deliver it.
Find the expensive workflow
We map where hours actually go and pick the workflow with the highest payback, not the flashiest demo.
Wire the tools with n8n
We connect your apps, APIs, and databases into a reliable pipeline with retries and error handling built in.
Add reasoning with LLMs + RAG
LangChain orchestrates OpenAI or Claude, grounded in your data through a vector DB, so answers are accurate and auditable.
Monitor, measure, hand off
We track what the automation saves, add guardrails, and hand you a system you can trust and extend.
The stack we use.
Proven tools, chosen for the outcome — not the resume.
Real builds, real results.
See how this work has played out for teams we've shipped for.
Questions teams ask before booking.
Anything repetitive with a clear trigger and rules: lead routing, invoice and document processing, report generation, inbox triage, data sync between tools, and customer-support deflection with RAG. If a person follows the same steps every time, it's a candidate.
We use retrieval-augmented generation (RAG). The model answers from your own documents and data in a vector database, with citations, instead of guessing. We also add validation and human-in-the-loop checkpoints for anything high-stakes.
Both. n8n handles orchestration and integrations fast, and we drop into Python and LangChain wherever the logic needs real engineering. You get the speed of low-code with the reliability of senior code.
Most engagements we scope target a 2–3 month payback by removing 70–90% of a specific manual workflow. On the discovery call we estimate the hours your team currently loses to that workflow and weigh them against the build cost, so you see the payback math before you commit.
We build with retries, error handling, and monitoring, and we document every workflow so it's maintainable. You own the system and can extend it without us.