Services

Practical services for AI, automation, and platform control.

in-box.ai helps organizations scope one real workflow, one AI workload, or one platform decision before committing to a larger program.

Where we help

Start with a decision or a controlled first project.

Each service is designed to replace vague transformation talk with a concrete assessment, pilot, or production-readiness plan.

Workflow Workhall workflow pilot

Map one approval, request, case, or operations flow and launch it as a governed no-code application.

Review Workhall implementation
RAG Enterprise RAG readiness

Assess documents, permissions, Arabic requirements, retrieval quality, citations, hosting, and governance before building an AI knowledge assistant.

Explore RAG service
AI cost AI infrastructure cost review

Baseline inference spend, GPU utilization, model routing, context usage, and sovereign deployment choices.

Review Cogniware.ai role
Agentic AI Agent readiness sprint

Evaluate one candidate agent against workflow ownership, tool access, policy controls, human approvals, and measurable outcomes.

Assess agent readiness
Platform control PaaS dependency review

Review renewal risk, portability, lock-in, pricing exposure, and whether the current platform still fits the operating model.

Review platform dependency
Industry Regulated workflow map

Identify a first workflow in banking, insurance, public services, healthcare, manufacturing, or utilities where governance matters.

Explore industry patterns

How a service starts

The first output should help you decide what to do next.

Problem framing

Define the workflow, workload, platform decision, users, data boundaries, and business owner.

Readiness check

Review process clarity, data quality, integrations, risk controls, and whether the use case is worth automating.

Architecture path

Choose the platform, hosting, integration, governance, and measurement model before build work starts.

Next-step plan

Leave with a scoped pilot, a stop/go recommendation, or a production-readiness roadmap.

Common mistakes

What we try to prevent before implementation begins.

Starting with a tool

Buying a platform before the workflow owner, exception path, and operating controls are clear.

Automating a broken process

Turning unclear approvals, duplicate data entry, or weak governance into a faster version of the same problem.

Scaling without cost visibility

Moving AI pilots into production without knowing model, GPU, context, and routing economics.

Bring one workflow, workload, or platform concern.

We will help decide whether it should become a Workhall pilot, RAG project, AI infrastructure review, agent sprint, or platform dependency assessment.