Add AI to Your Product
Without the Infrastructure
Your customers want AI features. Your team wants to ship them. But building LLM infrastructure is a distraction from your actual product. Connic lets you embed intelligent agents into your SaaS using skills you already have.
YAML
Agent config
Python
Custom tools
Git
Push to deploy
AI features your customers actually want
The hardest part of adding AI is not the AI itself. It is the infrastructure: deployment, scaling, monitoring, integrations. Connic handles all of that.
Semantic Search
Replace keyword search with natural language understanding. Users describe what they need and the AI finds it, even when exact words do not match.
"Find invoices from Q3 with payment issues" matches documents about billing disputes, payment failures, and overdue accounts.
Document Processing
Extract structured data from PDFs, contracts, and forms. Files uploaded to S3 trigger agents that parse, validate, and update your systems automatically.
Invoice lands in S3. Agent extracts vendor, amount, line items. Structured JSON flows to your accounting system.
In-App Assistants
Embed conversational AI that understands your product. Connect via WebSocket for real-time chat. Agents access your knowledge base and call tools you define.
User asks how to export data. Agent searches docs, finds the answer, responds with steps specific to their account.
Workflow Automation
Let users describe what they want in natural language. Agents break it down and execute using your tools. Schedule with cron or trigger from events.
"Send weekly signup summary to sales every Monday." Agent configures itself, queries users, formats report, sends email.
Integration without the integration work
Connectors handle the plumbing. Your backend triggers agents via webhooks, file uploads, database changes, or scheduled jobs.
Your app triggers
File upload, form submit, database change, or API call
Connector activates
Webhook, S3, PostgreSQL, or cron connector triggers the agent
Agent delivers
Process completes, results flow back through the same channel
What you skip by using Connic
Ship AI features with your existing team
You do not need to hire ML engineers or DevOps specialists. Focus on the features, not the infrastructure.
Ship in hours, not months
Write YAML config, Python tools, push to Git. That is the entire workflow. No Docker, no Kubernetes, no infrastructure to manage.
Use your existing team
No ML engineers or DevOps specialists required. If your team can write Python and use Git, they can ship AI features.
See everything
Every agent run tracked with full execution traces. See LLM reasoning, tool calls, timing, and costs. Debug issues in seconds.
Version everything
Agents live in your Git repo. Review in PRs, roll back with one click, maintain history. Your code, your control.
Secure by default
Secrets stored per environment. API keys never in code. SOC 2 compliant infrastructure. Enterprise-grade security without the work.
Scale automatically
Serverless execution handles any load. No capacity planning, no idle resources, no surprise bills. Pay only for what you use.