Planning and Cost Estimation

planning is where ai cost decisions are made, not after the bill arrives because amberflo has a built in rating engine and a complete ai pricing catalog, you can create accurate, model aware cost estimates before you ship a service, change an architecture, or commit to ongoing spend what planning is planning lets you build cost estimates for future services using the same pricing logic that amberflo uses for real usage you can estimate one time costs recurring usage based costs ai model usage non ai it services human and operational costs, like developer hours the result is a realistic forecast of what something will cost per month, per project, or over a defined time window when to use planning planning is designed for questions like what will this new chatbot cost per month? how much will production usage cost versus a pilot? what happens if we switch models or providers? what are the ongoing operational costs after launch? if the question is “what will this cost,” planning is the right tool building a plan a plan is made up of estimated services and costs, each with a usage pattern and timeframe estimating ai model usage you can add one or more ai models to a plan for each model, you specify provider and model usage unit such as tokens, seconds, images, or other model specific units input and output usage where applicable usage patterns each estimate can be defined as one time usage for example, a migration, backfill, or batch inference job recurring usage usage per hour, per day, per week, or per month this allows you to model both build time or launch costs ongoing operational costs timeframes and cost calculation every plan has a timeframe examples monthly cost for a production chatbot quarterly cost for a pilot one time cost for initial rollout amberflo uses the same rating engine as live usage to calculate input cost output cost total estimated cost for the timeframe this keeps estimates consistent with real billing and reporting adding other it services ai is rarely the only cost you can include additional services such as databases compute services storage networking any other metered it service each service can have its own usage estimate and billing unit this allows you to estimate the full cost of a service, not just ai spend including human and operational costs planning is not limited to metered services you can add custom cost items such as developer hours support staff platform operations hardware purchases licensing or fixed fees for each cost, you define quantity such as hours or units rate or unit cost one time or recurring behavior this makes planning useful for finance and leadership, not just engineers accurate pricing by default all estimates use the ai catalog pricing input and output rate differentiation your contracted prices, if configured if you have negotiated discounts with providers, those rates are applied automatically your estimates reflect what you actually pay, not list pricing what you get from a plan for each plan, you can see estimated cost by service estimated cost by ai model monthly or total projected cost this makes it easy to compare design options justify architecture decisions set budgets before launch why planning is different from guessing spreadsheets break because pricing changes input and output costs differ providers price the same model differently usage patterns evolve planning uses the same pricing logic as live usage, which keeps estimates aligned with reality key takeaway planning lets you answer cost questions before they become budget problems with amberflo planning, you can model ai and it costs accurately use real pricing, including contracted rates combine usage based and fixed costs make informed decisions before you build or scale this turns cost from an after the fact report into an upfront design input