ArrayFire AI Concierge
AI strategy that ends in working software.
Every business is being told to do something with AI. We help you decide what that something should be, prove whether it works with your real data, and turn the winners into reliable systems.
ArrayFire brings eighteen years of high-performance computing discipline to AI work: no hype, no vague roadmaps, and no open-ended consulting fog.
Choose the tier that matches where you are
From first question to hard engineering.
AI Opportunity Audit
For companies that know AI matters but do not know where to start. In two to three weeks, we deliver a prioritized list of 5-10 concrete opportunities.
- Discovery with operational, technical, and leadership teams.
- Use cases ranked by value, feasibility, cost, effort, and ROI.
- A recommended first project scoped for a visible 90-day result.
Proof-of-Concept Sprint
For teams ready to test one specific idea. In four to six weeks, we build a working prototype using your actual data and edge cases.
- One use case, fixed scope, fixed price.
- Honest evaluation of what works and where it struggles.
- A clear recommendation: scale it, refine it, or kill it.
AI Productionization
For companies with a promising pilot that needs to become a reliable, secure, cost-effective production system.
- Evaluation, monitoring, logging, alerting, and guardrails.
- Integration with CRMs, ERPs, ticketing systems, warehouses, and custom apps.
- Cost modeling, load testing, and capacity planning before surprises get expensive.
Custom AI Engineering
For work that public APIs cannot handle because of cost, privacy, latency, regulation, or domain-specific requirements.
- Self-hosted models, private cloud, and data-sovereign deployments.
- Inference optimization, quantization, batching, caching, and routing.
- Fine-tuning, edge AI, and regulated latency-critical systems.
Where we look for value
The audit turns AI possibility into a ranked business plan.
We study how the business actually runs, then separate useful AI from expensive theater. The best opportunities usually appear in four places.
Automate work people do today
Emails copied into systems, intake routing, invoice processing, scheduling, triage, and workflows that still need a human because the logic keeps changing.
Unlock the data you already have
Plain-language questions over spreadsheets, accounting records, CRMs, exports, and private systems, including on-site options when data cannot leave your walls.
Make your experts faster
AI does the first pass on quotes, proposals, contracts, equipment diagnosis, case files, reports, and memos so senior people can review instead of start from zero.
Improve customer response
After-hours calls, support backlogs, sales inquiries, quoting, pre-sales questions, and web interactions where customers wait, get stuck, or give up.
What the audit delivers
A fixed-price roadmap with honest tradeoffs.
Ranked opportunities
A written report identifying the best AI opportunities in your business, ranked by value and feasibility.
Cost, effort, and ROI
For each opportunity, we describe the work today, how AI changes it, what implementation takes, and what return is realistic.
What not to do
We call out ideas we recommend you avoid, and why. That section often saves more money than the project list.
A 90-day first project
One recommended starting point with scope, timeline, and budget sized to deliver a visible result.
Leadership readout
A 60-minute session with your leadership team to walk through findings, tradeoffs, and next steps.
What we can build after the audit
Prototype fast. Productionize carefully. Optimize when it matters.
Common proof-of-concept sprints
- Customer support assistants trained on your documentation and ticket history.
- Internal search across files, wikis, systems, and institutional knowledge.
- Document pipelines for contracts, invoices, claims, and applications.
- Sales lead enrichment, qualification, meeting summaries, and CRM workflows.
Production systems that can be trusted
- Evaluation frameworks so you know when the system improves or degrades.
- Monitoring, logging, alerting, safety layers, and security review.
- Model routing, caching, batching, and right-sizing to control spend.
- Load testing and capacity planning for real users and real traffic.
Custom AI engineering
When public APIs are too slow, too expensive, too exposed, or too generic, ArrayFire can move deeper: self-hosted models, private deployments, fine-tuning, edge AI, and latency-critical systems.
Why ArrayFire
We were making GPUs do hard things before AI became a boardroom word. That background matters when performance, privacy, cost, and reliability decide whether an AI system survives production.
Start with a conversation
Not sure where you fit?
Tell us what you are trying to improve. We will tell you which tier makes sense, including whether you do not need us yet.
