Frequently asked questions

Answers that build confidence. What you need to know to move forward with AI.

About Ainfore

What does Ainfore do?

Ainfore delivers AI-enabled forecasting, marketing intelligence, and decision support—from dashboards and reporting to agents and copilots—so teams can act faster with traceable evidence and governed workflows.

Who is Ainfore best for?

How is Ainfore different from generic AI tools?

Products and what you deliver

What types of AI solutions do we offer?

We offer:

Forecasting solutions (project-based or ongoing refresh/monitoring)
Market & competitor intelligence (pulse reporting, tracking, alerts)
Voice of Customer intelligence (reviews, surveys, tickets → actions)
AI agents and copilots for operational workflows
Chatbot development (support, lead qualification, booking)
Automation workflow builder (approvals, routing, exceptions)
Web App Agent Platform (RBAC, audit logs, governance)
AI Ops Monitoring & Optimization (production reliability)
Custom solutions (scoped to your workflows, data, and governance requirements)

Do we sell one-time projects or subscriptions?

Can we start small?

How implementation works

What does onboarding look like?

Typical flow: discovery → define scope and success metrics → configure sources/permissions → build and test → user training → go-live.

How long does it take to launch?

Do you integrate with our systems?

Security, privacy, and governance

Do you train AI models on our data?

No. Your data is used only to deliver your service and is not used to train public models. We work within your approved sources and access controls, and we can support bring-your-own model (OpenAI/Azure OpenAI) if preferred.

Do you support role-based access and audit logs?

Can we use our own model account (BYO OpenAI/Azure OpenAI)?

Pricing, usage, and overages

What’s included in the price?

Each tier includes a defined scope (e.g., users, workflows, sources, refresh cadence, and support). The Statement of Work confirms final scope.

How does AI usage work?

What happens if we exceed scope?

ROI and measurement

How do you measure ROI?

At kickoff, we agree on 1–3 success metrics and capture a simple baseline. Then we measure improvement during the pilot and after launch using usage and outcome data. Common ROI metrics include hours saved, cycle-time reduction, fewer escalations or rework, improved conversion, fewer errors, and faster reporting—along with adoption (active users, runs, and completion rates).

What results should we expect?

Most teams see early gains in speed and effort reduction—faster turnaround on recurring tasks, fewer manual steps, and more consistent outputs. As adoption grows and workflows are tuned, benefits typically expand to fewer escalations and errors, better decision quality, and more proactive reporting. We validate impact against the agreed KPIs during the pilot and track progress after launch.

Support and ongoing optimization

Do you offer ongoing support after launch?

Yes. We offer ongoing support through Managed Optimization and AI Ops Monitoring & Optimization. This can include performance monitoring, quality checks, controlled updates and versioning, knowledge/source refreshes, issue triage, and regular reporting—so your solution stays reliable as your data, policies, and business needs change.

What is AI Ops Monitoring & Optimization?

Getting started

What do you need from us to begin?

Use case, success KPIs, sample inputs/outputs (sanitized), and approved data sources/access contacts—no sensitive data required to start.