[00] Pricing
Indicative budgets from our published ranges, four ways to work with us, what moves the price and what you pay after launch. Discovery, scoping and the written proposal are free.
projectAI chatbot that answers from your documents
More channels, languages or systems move it up the range
example draft · published ranges · fixed quote after scoping
engagement models
Most clients combine them over time, for example a proof of concept now, a fixed-scope build once it proves itself and a support plan after launch.
A short, fixed-price project that runs one use case on your own data and measures it against a baseline we agree up front. You see real accuracy, speed and running cost before deciding on a full build.
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We scope the use cases, data sources, integrations and accuracy targets with you, then quote a one-time price and timeline. Delivered in phases so you see working software early.
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A monthly retainer for AI, data and software engineers plus a project lead who work only on your product. Scale the team up or down each quarter.
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Keep models accurate as your data changes. Plans cover monitoring of accuracy, cost and usage, fixes, model and library updates, retraining and a bank of hours for small improvements.
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indicative budgets
Use these for planning. Where a project lands in its range depends on the eight factors below. The estimator places yours in a third of the range in about a minute.
Estimate your budgettier.01 small
$10k – $50k
usually
tier.02 medium
$50k – $200k
usually
tier.03 enterprise
$200k+
usually
In US dollars, for the one-off build. Model usage, hosting and taxes are extra. Indian clients are quoted in INR. Source:our AI and ML services guide.
what drives cost
Knowing these before the first call helps us give you a realistic range faster.
Answering questions from a handful of documents is simpler than an agent that works across several systems and makes decisions.
Lower cost: One task, such as answers from documents
Higher cost: An agent deciding across several systems
Scattered spreadsheets, scanned files and unlabelled images need collection, cleaning or annotation before a model can use them.
Lower cost: Clean and in one place
Higher cost: Needs collecting or labelling
Self-hosted open-source models and fine-tuning cost more to set up, but can lower running costs or keep data in-house.
Lower cost: A hosted model through an API
Higher cost: Self-hosted or fine-tuned models
The higher the accuracy you need, the bigger the evaluation set, the more testing rounds and the more human review.
Lower cost: Internal use, staff check the output
Higher cost: Regulated or high-stakes decisions
Legacy systems, ERPs without APIs and on-premises databases take more work than documented APIs.
Lower cost: None, or one modern API
Higher cost: Many systems, or legacy without APIs
Thousands of requests a day need caching, queueing and cost controls that a pilot for one team does not.
Lower cost: One team
Higher cost: Customer-facing at high volume
Data residency, on-premises deployment and audit logging add scope compared with a standard cloud set-up.
Lower cost: Standard cloud set-up
Higher cost: On-premises, single sign-on, audit logs
Dashboards, approval queues and admin screens add design and build work on top of the AI itself.
Lower cost: An API another system calls
Higher cost: A full web app with approval queues
in the price
Unlike most software, AI has usage costs that grow with how much it is used. Every proposal estimates them up front, and we design systems to keep them down.
Calculate your ROIModel usage
paid to The model provider, usually on your own account
Grows with the number and length of requests; caching and smaller models keep it down
Cloud hosting
paid to Your cloud account or ours
Servers, vector database and storage; GPUs only if models are self-hosted
Monitoring and retraining
paid to Optional AppsInAi support plan
Accuracy checks, updates and retraining as your data changes
Third-party tools
paid to The tool vendor
For example BI, RPA or labelling platform licences, where used
How we quote
The first three steps are free and usually take under two weeks, so you know exactly what you are buying before any work starts.
Every project starts with a free, no-obligation consultation.
$ appsinai quote --fixed-price
A free 30-minute call to understand the problem, the data you have and the systems AI would need to work with.
You get: honest view on fit · a first budget range
We look at samples of your data and agree the use cases, integrations and accuracy targets in scope, and what can wait for a later phase.
You get: scope document · phase plan
A fixed price and timeline for the agreed scope, with payment milestones tied to deliverables, an estimate of running costs and support options.
You get: fixed quote · timeline · running cost estimate
Most projects start with a pilot. You see results at the end of each phase and pay as milestones are met. Changes are priced before they are built.
You get: milestone releases · no surprise invoices
$
FAQ
Straight answers to what buyers ask us most. Can't find what you need?
Email sales@appsin.ai or call +91-9025555584.
Ask us directlyWe publish indicative ranges. Small projects such as a chatbot or a basic predictive model usually fall between $10,000 – $50,000, medium projects such as recommendation engines and analytics platforms between $50,000 – $200,000, and enterprise platforms at $200,000 and up. A fixed price comes after a short call and a look at your data, because the same chatbot can be a website assistant answering from twenty pages or a multilingual agent connected to your CRM, ERP and helpdesk.
Try the AI project cost estimatorA proof of concept is a small fixed-price project scoped to one use case, usually 3–6 weeks long. The price depends on how ready your data is and how many systems it touches. We give you a range on the first call and a fixed quote after the data review.
Then you have paid for a small pilot, not a full build. You get the evaluation report with the measured results and our honest view on whether to continue, change the approach or stop. Going ahead is your decision, and the pilot does not commit you to a full build.
No. The discovery call, the data and scope review and the written proposal are free and carry no obligation.
Usually you do, directly to the provider on your own account, so there is no mark-up and you keep control of the keys and data settings. We estimate running costs in the proposal and design the system to keep them down.
You do. On completion and final payment, the code, prompts, trained or fine-tuned models, datasets and documentation we build for you are handed over, as set out in the contract. Third-party and open-source models stay under their own licences.
Fixed-scope projects are split into milestones, typically a deposit at kick-off and payments as each phase is accepted. Dedicated teams and support plans bill monthly. We work on a one-time project cost, not equity.
INR for Indian clients and USD for international clients. Other currencies can be agreed for clients in the Middle East. The indicative ranges on this page are in US dollars.
Get a quote
Share the problem you want to solve, the data you have and the systems you use. We reply within one business day with a realistic range and a suggested next step.
