We build agentic AI systems that run in your organization.
What we build
Most organizations have fragmented data sitting in disconnected systems. Reports get pulled manually. Decisions get made on instinct. Waifinder builds the intelligence layer that sits on top of your existing data and makes it work for you automatically — pipelines, intelligence agents, and conversational assistants configured for your workflows.
Not demos. Not prototypes. Production systems.
How it works
Scoping call — we map your data, your workflows, and your biggest operational gaps. No pitch, just diagnosis.
Proposal — fixed-price proposal within 48 hours. Scope, architecture, timeline, cost.
Build — typical first deployment is four to six weeks.
Managed service — we stay on as your AI operations partner. With a feedback loop in place, the system gets smarter over time.
Get started
No pitch. No commitment. Just a 30-minute conversation to understand your situation.
We'll tell you honestly whether we can help and what it would look like.
The Project Plan
With Waifinder, you are not hiring a consultant. Our process is we scope your project, sign a fixed-price contract, and 90 days later you have a production AI system built specifically for your business — plus the option to hire the team that built it.
PHASE 01
Discovery — Week 1
You describe the problem. CFA's technical lead translates it into a precise specification. You see exactly what will be built, what it will do, and what it won't do. No ambiguity. No scope creep.
Deliverable: Technical specification and project plan. No cost at this stage.
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PHASE 02
Contract — Week 2
Fixed price. Fixed scope. Fixed timeline. $65,000 for a 90-day production build. You know exactly what you're paying and what you're getting before you sign.
No hourly billing. No change orders. No surprises.
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PHASE 03
Build — Weeks 3–14
A supervised team of trained AI engineers builds your system. Weekly updates. You see progress every week. The system is built to your specifications, tested against your data, and deployed to your environment.
You stay informed. You don't have to manage. That's what the PM is for.
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PHASE 04
Delivery — Week 14
You receive a production-deployed AI system, complete documentation, and a handoff session. The system runs. You own it. And you've watched the team that built it work on your problem for three months.
All that’s left is to choose a Maintence Model to ensure your new system is learning and adapting to your feedback.
Use case example
Workforce Solutions Borderplex needed real-time intelligence on AI skills demand across the El Paso, Las Cruces, and Ciudad Juárez region. Waifinder built a six-agent pipeline that ingests live job postings, extracts AI-related skills, enriches each posting with demand signals, and serves the intelligence through a plain-language query interface. 2,676 job postings processed. Eight sectors covered. Live in production.
Tech stack: Python, PostgreSQL, Google Gemini Flash, Azure, Next.js, FastAPI.
Use case example
Computing for All needed to unify 5,000+ records, employer relationships, placement outcomes, and grant financials spread across five disconnected systems. Waifinder deployed its agentic operating system to run CFA's internal operations — candidate pipeline management, BD lead scoring, grant financial reconciliation, and consulting intake. Staff now have personalized assistants that surface the right information on demand.
Tech stack: