AI integration for US companies and product teams

Two kinds of US buyers

The first is an operations lead at a services or ecommerce company who wants fewer manual steps between tools. The second is a product team at a software company who wants AI features inside their app, such as summaries, search or draft generation. We serve both, with different designs.

For the first buyer, the work is workflow integration with n8n, Make or a small service. For the second, it is API integration in the product's own codebase, with streaming, error handling and cost controls.

Whichever kind of buyer you are, we start with a single workflow that has a clear owner and a measurable result. Wider rollouts are easier once the first one has run for a month and the numbers are visible.

Typical integrations

If you are not yet sure what to connect, start with AI consulting for the US.

Many US clients also have a tool nobody remembers buying. Before building, we check whether your CRM, helpdesk or office suite already includes an AI feature that does the job. If it does, we say so and save you the build fee.

For product teams, the design includes streaming responses, retries, timeouts and a fallback message when the provider is slow or down. These details decide whether the feature feels reliable to customers.

Security and compliance expectations

• Vendor questionnaires. US customers often ask for SOC 2 reports, data retention terms, whether data trains models and breach notice terms. We document the provider answers and the date checked.
• State privacy laws such as California's CCPA add notice and rights duties when personal data is used. Check which laws cover your customers.
• HIPAA. If you handle protected health information, the model provider and any platform must offer suitable terms before PHI is used. Otherwise, keep PHI out of the flow.
• FTC. Describe AI features accurately. Overclaiming what an AI feature does can draw attention.
• Our access. We work with test data and read-limited credentials, logged and removed at handover.

Confirm legal points with your counsel. The AI agent security checklist covers permissions and logging.

Build process

1. ScopingOne workflow or feature, with inputs, outputs and approval points.
2. Design noteModel choice, prompts, data fields, error handling and cost per run.
3. BuildWeekly demos on staging.
4. EvaluationA test set from real cases and an agreed accuracy bar.
5. Launch and monitorGradual rollout, with logs and alerts.

We work in your hours. Eastern 09:00 is 18:30 or 19:30 in Pune, and Pacific 08:00 is evening for us. Liftup Technologies has an office in New York, but delivery is by our team in Pune. One lead developer owns the project.

Costs after launch

A US operations lead should know the monthly cost before approving a build. The quote includes a table like this one.

We set cost caps in the model account so a bug cannot create a surprise bill. For product features, we add per-customer limits as well.

If your team is on the West Coast, we keep calls short and send written updates at the end of your day so you can reply before the next one.

Price

Projects start at $1,500 and our rate is $30 an hour. A single integration sits near the start of that range, while product features with evaluation and fallback logic take more hours. The AI integration cost guide lists the drivers. A fixed quote arrives within one working day of a short call.

Running costs, such as model usage and platform fees, are separate and estimated in the quote. Sales tax does not usually apply to services bought from abroad, but check with your accountant. See the US AI page for related services.

Sales tax rules for digital services vary by state and apply to the seller, not to this work, but ask your accountant if you resell the feature.