AI Automation & Workflows
Put your repetitive, high-volume work on autopilot, with humans in the loop where it counts.
Automate the busywork, keep the judgment.
We map the processes eating your team's hours and rebuild them as reliable, monitored automations, connected to the tools you already use.
- Process discovery and mapping
- Workflow automation design
- Tool and API integration
- Human-in-the-loop checkpoints
- Monitoring, logging, and alerting
- Iteration and optimization
Common automations.
- Lead intake, routing, and enrichment
- Document processing and data entry
- Reporting and dashboard generation
- Customer and internal Q&A
- Follow-up and nurture sequences
See if AI Automation & Workflows is the right move for your team.
Request a free quoteWe Build and Operate Your AI Workflows
We build hands-on automation that runs your real business processes, then we manage it day to day. Using LangGraph, CrewAI, and n8n alongside Claude, GPT, and open models, our senior engineers connect your CRM, billing, support, and data systems into workflows that actually hold up under enterprise load. For managed engagements, this is production automation we own and operate day to day; we can also hand off a documented, owned-by-you workflow with training.
We monitor every workflow in production and remediate within the agreed support scope when an upstream system changes, so automation keeps running reliably without your team babysitting it.
- We design and ship end-to-end workflows across CRM, support, finance, and ops with n8n, LangGraph, and CrewAI
- We wire AI steps into real systems with retries, human-in-the-loop checkpoints, and audit logs
- We handle versioning, monitoring, and error handling so automations stay reliable at scale
- We tune model choice per step, from Claude and GPT to Llama, Hermes, and Mistral, for cost and accuracy
Reliable by design.
Every automation ships with monitoring and fallback paths, so it runs every day under real conditions, not just in a demo.
Questions, answered.
We start with a process discovery session where we map the work your team actually does, then score each task by volume, repeatability, and error cost. Tasks that are high-frequency and rules-based get prioritized, while anything requiring real judgment stays human or becomes a human-in-the-loop checkpoint. For example, lead intake and enrichment usually automates cleanly, while approving a discount over a threshold gets routed to a person for sign-off.
It is a deliberate pause where the automation hands a decision to a person before continuing, instead of acting blindly. We place these wherever a wrong move is expensive or hard to reverse, and surface the choice in a tool your team already uses like Slack, email, or your CRM. For example, an AI agent can draft and enrich a customer reply, but a rep approves or edits it in one click before it sends, so you get the speed without losing control of the message.
Every workflow we ship includes monitoring, logging, and alerting plus a defined fallback path, so a failure routes the task back to a human or a retry queue rather than silently dropping it. You get alerted when something needs attention, and the logs tell us exactly where it stopped. This is the difference between an automation that works in a demo and one that runs every day under real data and real load.
Yes. We build on top of your existing stack rather than asking you to replace it, integrating through APIs and connectors to your CRM, help desk, spreadsheets, databases, and internal apps. We assemble these with orchestration frameworks like n8n, LangGraph, and CrewAI so the logic is maintainable, not a pile of brittle scripts. If a system has no clean API, we will tell you upfront and design around it.
Either way, we make that explicit before we build. NYFTY can hand off a documented, owned-by-you workflow with training, or we can manage and run it as an ongoing service, watching the monitoring, tuning prompts and rules, and handling edge cases as your volume changes. Most clients start with us running it while the automation stabilizes, then decide on long-term ownership once it is proven in production.