Netofficials provides AI integration services that connect AI models to the products and platforms you already run, including CRMs such as Salesforce and clinical systems such as EHRs. A written discovery scope, a named delivery lead and a review after every sprint keep the work accountable. Send a short brief to begin.
We start with a written discovery scope that names the workflow, the data the model will touch and the systems it must connect to, such as Salesforce or an EHR. You see the open questions and an initial estimate before committing, and where AI is not the right fit, we will say so after scoping.
Our technical architect is accountable for system design, technology selection and code quality standards. You review user flows, interface designs and architecture notes, including how model outputs, fallbacks and human checks fit the workflow, before engineering begins.
One cross-functional team builds the integration, tests it and deploys it, with a named delivery lead owning day-to-day progress. You review at the end of every sprint, and at release you receive documentation and deployment access.
We work with you to pin down which workflow the AI should improve, which systems it must connect to (a CRM such as Salesforce, an EHR, your own product) and what data it will touch. You review the written discovery scope and decide what belongs in the first release.
You receiveYou agree the written discovery scope
Our technical architect lays out how the AI model connects to your systems, where data flows and how failures or low-confidence answers are handled. You walk through the user flows and the integration design with us.
You receiveYou approve the design before development starts
The cross-functional team builds the integrations and AI features in sprints, working from the scope you agreed and testing against your systems in staging. Your named delivery lead keeps you informed on progress between reviews.
You receiveYou review working software at the end of every sprint
QA checks the integrated workflow end to end, including the model's outputs, error handling and connected-system behaviour. You test the result against the acceptance criteria written into the scope.
You receiveYou accept the integration against the agreed criteria
We deploy the AI integration into your production environment. Your team then receives the documentation and deployment access needed to run it and extend it.
You receiveYou confirm the handover of documentation and access
Send a short brief naming the product or system you want AI connected to, and we reply with questions, a proposed scope and the team we would put on it.
List the platforms the AI has to read from and write to, such as your own product, a Salesforce CRM or an EHR system. Each connection brings its own access rules, data formats and testing needs, so it moves cost and timeline more than the model choice does. We map them in the written discovery scope, so you see the real size of the work before you commit.
Decide which records the model may use, where they are stored and who is allowed to see the output. Customer and patient data may call for masking, role-based access or a mutual NDA before we see samples. Settling this early prevents rework once the build is under way, and our technical architect is accountable for how it is designed.
Agree up front how you will judge whether the AI feature works: acceptance criteria, the cases QA will check and who signs off. You review a working build at the end of every sprint. At release we hand over documentation and deployment access, so your team can run and extend the integration.
Fixed-price delivery of a defined AI integration, such as connecting a model to your product or to Salesforce, suited to buyers who can state the outcome up front.
A dedicated India-based team that keeps extending AI features across your systems sprint by sprint, suited to a roadmap that will keep changing.
Engineers with AI integration skills who join your in-house team and follow your tools, suited to buyers who already have delivery management in place.
Netofficials confirms the AI approach, model or API choice and the supporting stack in the written discovery scope, before any build begins. The choice depends on the systems you already run, such as a Salesforce org or an electronic health record platform, on the data the AI may use, and on who will maintain the integration after release. You see the reasoning up front, which removes late rework and surprise dependencies. If AI is not the right fit, we will say so after scoping and recommend another approach.
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PostgreSQLCost and timeline are driven by the systems the AI must connect to, the quality and access of your data, and how much testing the use case needs. A single AI feature added to one product is a smaller job than automation that spans Salesforce, an EHR system and an internal tool, because each connection brings its own authentication, data mapping and QA. We give no price before we have seen your brief. Netofficials produces a written discovery scope with an initial estimate, and you can then choose fixed-price project delivery, a dedicated India-based team or staff augmentation.
You own what we build for you: IP assignment is confirmed in the contract before the build begins, and you receive documentation and deployment access at release. For data, we agree what information the AI may see, and where it is processed, during discovery, before any build starts. If your material is sensitive, we can sign a mutual NDA before you share details. Our technical architect is accountable for system design, technology selection and code quality standards.
Yes. AI integration is about fitting into the software you already run, so we shape the work around your current engineering team, tools and platforms, including CRMs such as Salesforce and clinical systems such as EHRs. We agree the communication window, meeting schedule and update cadence before work begins. A named delivery lead owns day-to-day progress, and you review the work at the end of every sprint. If we think another approach would serve you better, we will say so after scoping.
Tell us which product, CRM or clinical system the AI needs to work inside, and what you want it to do. We reply with questions and a written scope, so you can judge the approach, the team and the next step before any build begins. If another approach would serve you better, we will say so after scoping. Netofficials runs the work through one cross-functional team, with a named delivery lead as your point of contact.
