AI agent development for real business workflows
Custom AI agents that read, decide and act inside the tools your team already uses, with guardrails, logging and human approval where it matters.
SixSol designs and builds AI agents that do useful work: qualifying leads, answering customers, preparing documents, updating your CRM and coordinating tasks across systems. We build on leading large language models such as OpenAI GPT, Anthropic Claude and Google Gemini, or on open-source models when your data must stay on your own servers.
What an AI agent can do for your business
- Sales agents that qualify inbound leads, answer first questions, book meetings and update your CRM.
- Customer support agents that answer from your documentation, escalate edge cases and hand over to a person with full context.
- Operations agents that schedule technicians, process orders, reconcile records or prepare daily briefings.
- Document and research agents that read PDFs, emails and websites and return structured, sourced summaries.
- Multi-agent workflows where specialised agents pass tasks to each other under a supervisor, with a full audit trail.
How we build agents that hold up in production
- Map the workflow. We document the task, the decisions, the systems involved and what “done” looks like.
- Connect your tools. APIs, databases, CRMs, helpdesks, Google Workspace, Microsoft 365, WhatsApp and webhooks.
- Ground the agent in your data. Retrieval-augmented generation (RAG) over your documents, so answers come from real sources.
- Add guardrails. Permission limits, approval steps for risky actions, input validation and safe fallbacks.
- Measure, then scale. Logging, test sets and evaluation show accuracy, cost per task and response time before you roll out.
Typical technology stack
Python and TypeScript, LangChain and LangGraph, OpenAI and Anthropic APIs, Model Context Protocol (MCP) tools, vector search with pgvector or Pinecone, n8n or Make for orchestration, and hosting on AWS, Google Cloud or your own infrastructure.
Agents inside your apps and devices
Because SixSol also builds mobile apps, backends and embedded hardware, your agent does not have to live in a chat window. It can work inside your app, respond on WhatsApp, run as an n8n workflow, or use local AI on a device that works offline.
How long does it take to build an AI agent?
A focused agent for one workflow usually reaches a working pilot in 2–6 weeks. Agents that touch many systems or need strict approvals take longer. We agree milestones with a demo at each one.
How much does AI agent development cost?
It depends on the number of integrations, data sources and approval steps. Our AI agent development cost guide explains typical ranges and running costs.
Will our data be used to train AI models?
Under their published business terms, the major model providers do not train on API data by default. When data must stay in-house, we can deploy open-source models on your own infrastructure.
Can the agent hand over to a person?
Yes. We design escalation rules so the agent passes a conversation or task to your team, with full context, whenever confidence is low or an action needs approval.