AI Agents & Automation That Ship | Voice AI, LLMs, .NET
Not every automation needs an LLM. A B2B business was receiving purchase orders from retailers through SPS Commerce.
Someone on the team then checked stock by hand, retyped each order into Sage 50 as a sales order, and kicked off fulfillment.
We built a platform on ASP.NET (http://ASP.NET) Core and C# that handles it end to end.
→ Purchase orders come in through SPS Commerce automatically
→ Stock and order details are validated before anything is created
→ Sales orders land in Sage 50 without retyping
→ Anything odd is flagged as an exception instead of quietly slipping through Less manual work across the whole order lifecycle, cleaner data, and orders that keep moving without anyone copying fields between screens.
I build a lot of AI agents now. But the first question on every scoping call is still the same.
Does this need judgement, or does it just need wiring? Half the time it's wiring.
0
54
Most AI features never leave the demo.
The model is rarely the problem. It's everything around it: messy data, old .NET code nobody wants to touch, and no clear answer to "what does this actually save us?"
On CasePath we skipped the chatbot and aimed AI at one job caseworkers hated: writing case notes.
Result: 90% less documentation time. Supervisor decisions 83% faster. 20% more caseload with zero new hires.
What made it work:
Pick one painful task, not a whole "AI strategy"
Put AI inside the app people already use
Measure hours saved before writing a line of code
If you run a .NET product and AI is on your roadmap, message me. One call and I'll tell you where it'll pay off, and where it won't.
1
137
An AI agent that can move money is only useful if it can't move it on its own.
Haia lets people manage their banks, crypto wallets and brokerages from one place, just by saying what they want done.
I built the AI orchestration layer. The interesting design choice wasn't the model. It was deciding where the model is not allowed to act.
→ The agent turns a request into a step by step plan
→ Each step is routed to the right banking API, wallet, chain or brokerage
→ Security and compliance checks run before anything executes
→ The user approves every move, and transactions are signed on their own device It's fully non-custodial.
Zero private keys ever exposed, to us or to the model.
If you're building agents that touch money, health records or anything you can't undo, design the approval step first. Then the AI.
1
1
128
Senior Full-Stack (RoR, Python, Node, PHP) Developer
- 5.0
- Rating
- 6
- Followers
Senior Full-Stack (RoR, Python, Node, PHP) Developer
Full Stack Dev | ASP.NET, Angular, SQL Server
Full Stack Dev | ASP.NET, Angular, SQL Server
View more →
Senior AI Engineer & Full Stack Architect
Senior AI Engineer & Full Stack Architect
Senior Full-Stack Engineer building scalable applications
New to Contra
Senior Full-Stack Engineer building scalable applications
The system architecture uses a robust tech stack for a high-performance, scalable web app dashboard. React enables efficient UI development with its component-based approach. Next.js, built on React, offers server-side rendering for faster initial loads. Microsoft IIS ensures reliable, secure deployment, while SQL Server provides structured, efficient data management.
0
71
An application in which different entities in hospital have their portals where they can login and
perform their daily tasks related to appointments. Schedules of providers and physicians can k handled
through this app. Hospital employee can schedule patient’s appointments that could be phone
consultation, pre-Op or post-Op appointment. This app also has the call center module where call center
agents can receive and dial call to patients from their portal. Employee can check and create new
patients. Employee can also collect payments from patient through this application.
0
71
Sr. Software Engineer
Sr. Software Engineer
Full Stack .Net Developer 🚀
Full Stack .Net Developer 🚀
View more →