We build AI agents that read requests, pull data from your systems, decide the next step and act on it, and pass anything outside their remit to a person.
Each agent is connected to your ERP, CRM and internal tools, grounded in your data with RAG, limited by explicit guardrails and eval-gated every release.
Agents work best on tasks where people read variable information, gather data from several places and coordinate the next step.
Information-heavy finance work, prepared for your team to approve.
Payments and postings stay with your finance team.
Answers and actions grounded in your own data.
Below the confidence threshold, a person takes over.
Coordination across orders, suppliers and stock.
Every tool call is logged and replayable.
The agent reads each incoming ticket, retrieves answers from OctoLabs' documentation with RAG, replies with cited sources and escalates to the support team when confidence is below the threshold.
| Capability | Traditional automation | AI agent |
|---|---|---|
| Fixed rules | Yes | Yes, when a rule is enough |
| Variable input (emails, PDFs, free text) | Limited | Reads and interprets it |
| Choosing the next step | Follows a predefined path | Decides from context, using only its tools |
| Data from several systems | Through configured integrations | Calls connected tools and RAG |
| Unexpected input | Fails or needs a predefined branch | Handles it or escalates below the threshold |
Predictable process with fixed rules? A workflow is cheaper and simpler. We build that instead.
Business process automationAn agent is only useful when it can reach the data and tools its task needs, and nothing more.
Claude, GPT or open-weight models, chosen per task on quality, latency and cost.
Hybrid retrieval over your documents and databases, with cited answers.
Scoped API access to your ERP, CRM, accounting and ticketing systems.
LangGraph or first-party SDKs, with state persistence and replay.
Permission scopes, confidence thresholds and human approval on high-impact actions.
Traces for every tool call, drift monitoring and eval-gated releases.
We pick one operational task, map how it runs today and decide which steps need a person.
We define the agent's tools, data sources, permissions, guardrails and escalation rules.
We build the agent and connect it to your systems through scoped APIs.
We build a held-out evaluation set from your real requests. A failing score blocks the deploy.
Traces, drift monitoring and access logs in production; we improve the agent from real usage.
A business AI agent is software that reads information, decides the next step and takes action in your systems through the tools it is given. Unlike a chatbot, it does work: it retrieves records, compares documents, updates tickets and prepares decisions for people to approve.
A chatbot answers messages. An agent also retrieves data from connected systems, calls tools, takes the actions it is permitted to take and coordinates multi-step work. What it may do is set by its tools, permissions and guardrails.
Yes, through their APIs or other integration interfaces. The agent gets scoped access: it can read and change only what its task needs, and every call is logged.
They handle the information work: invoice analysis, document comparison, reconciliation support and exception flagging. Payments, postings and approvals stay with your finance team.
They are as safe as their guardrails: scoped permissions, human approval on payments and other high-impact actions, audit logs, and an evaluation set every release must pass. Agents still make mistakes, which is why every action is traced and reviewable.
It depends on the task, the number of systems the agent connects to, data access, security and testing. A focused agent for one operational task is a very different scope from a multi-agent system across departments, so we assess the use case before estimating.
The engineering behind this solution: architecture, tech stack and delivery process.
If your team spends hours gathering information, investigating exceptions or coordinating tasks across systems, an agent can take on part of that work.
Tell us which task you want to improve, how it works today and which systems are involved.
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