AI Development Company in the USA
B2C Info Solutions is an AI development company in the USA that turns data and ideas into working artificial intelligence systems for businesses across North America. We build machine learning models, generative AI applications, AI agents and AI-powered apps — and run them in production so they keep delivering value. Building digital products since 2014, with a New York footprint for US time-zone delivery.
- Time-zone aligned US delivery
- HIPAA, SOC 2 & CCPA aligned
- Full IP ownership, by contract
Why US businesses choose B2C Info Solutions
American enterprises and funded startups are past asking whether to use AI. The real question is which partner can ship it safely and make it pay back. We pair more than a decade of product engineering with applied AI, so you get a team that understands both the model and the business outcome behind it.
Time-zone aligned delivery
Teams that work in your business hours with daily standups and clear reporting, so US clients never wait overnight for answers.
Compliance and security first
HIPAA, SOC 2, CCPA and GDPR-aware engineering, US cloud data residency and signed IP ownership — built in from the start, not bolted on later.
Transparent commercials
Fixed-scope or milestone-based engagements so cost and timeline stay predictable. No surprise overruns.
Full lifecycle ownership
From AI strategy and data readiness through model building, integration and ongoing MLOps operations, one accountable team end to end.
Product engineering plus AI
Unlike AI-only consultancies, we combine AI with web, mobile and enterprise engineering under one delivery team, so the model and the product around it are built together.
Building digital products across three continents
The right discipline for each part of the work
Rather than stretching one generalist across a project, you get specialists who are hard to hire and costly to keep elsewhere, available immediately without months of recruiting.
ML Engineers
Design, train and tune the models behind prediction, recommendation and scoring.
Data Scientists
Shape raw, messy data into features, insight and the metrics that prove a model earns its place.
AI Agent Developers
Build multi-step agents that act across your systems within defined guardrails.
NLP Engineers
Deliver language understanding for search, voice, chat, classification and summarization in English and beyond.
Computer Vision Engineers
Build recognition, visual inspection and document-reading systems from images and video.
MLOps Engineers
Ship, watch and retrain models so they stay dependable and accurate in production.
Our AI development services in the USA
We offer a complete range of AI development services, from a single model to an end-to-end intelligent product. Every engagement starts with your business problem, not the technology.
AI Consulting & Strategy
We assess your data, use cases and constraints, then deliver a practical AI roadmap with prioritized use cases, a clear architecture and a realistic budget. This is where most durable AI projects begin, because it ties each build to a measurable outcome.
- Data and readiness audit
- Use cases ranked by impact and feasibility
- Costed roadmap and target architecture
Generative AI Development
We build generative AI on large language models — private assistants, knowledge and document search, content generation — grounded in your own data so outputs reflect your business rather than the open internet.
- Domain-tuned assistants and copilots
- RAG with Pinecone, FAISS or pgvector
- Guardrails matched to your risk appetite
AI Agent Development
We design AI agents that complete multi-step tasks rather than just answering one question. An AI agent can triage a support ticket, pull data from connected systems, draft a response and route exceptions to a person, reducing manual handling across operations and back office work.
- Multi-step task execution
- Human-in-the-loop escalation
- Reduces manual handling in support & ops
Machine Learning & Predictive Analytics
Our machine learning teams build predictive analytics for forecasting, recommendation, churn, fraud detection and anomaly detection, then deploy and monitor those models so accuracy holds up against real, changing data.
- Forecasting and demand prediction
- Fraud, churn and anomaly detection
- Dashboards managers can act on
AI-powered App & Product Development
With deep mobile and web engineering DNA, we build AI features directly into mobile and web apps — recommendation, personalization, computer vision and voice interfaces that users actually feel.
- In-app recommendations and visual search
- Embedded assistants in your product
- Web and mobile, end to end
NLP & Computer Vision
We build natural language processing for classification, extraction, summarization and conversation, and computer vision for image and video understanding, visual inspection and document processing.
- Text classification, extraction & summarization
- Document reading & visual inspection
- Object recognition and video analytics
AI Integration & MLOps
We connect models to the systems you already run — CRM, ERP and data warehouse — through secure APIs, then operate them with MLOps, monitoring and retraining so they do not silently degrade after launch.
- Secure APIs into CRM, ERP and data warehouse
- Versioning, monitoring and retraining
- No quiet model drift
AI development use cases by US industry
Accurate models and fast adoption come from real domain context. These are concrete ways US organizations put AI into production.
Healthcare
A US health system uses a RAG assistant over clinical guidelines and physician notes to cut documentation time, while a computer vision model flags priority cases in radiology queues. Both run inside a HIPAA-compliant environment with audit logging, so clinicians spend less time on paperwork and more on care.
Fintech & Banking
A lender deploys real-time machine learning for transaction fraud detection and an explainable underwriting model that supports fair-lending review under ECOA. A generative AI support assistant answers account questions with strict guardrails, all within a SOC 2 aligned setup, lowering fraud loss and support cost together.
Retail & Ecommerce
An online retailer combines a recommendation engine with demand forecasting to lift average order value while cutting overstock and carrying cost. Visual search lets shoppers find products from a photo, and generative AI drafts product descriptions at catalog scale for human review.
Logistics & Supply Chain
A logistics operator uses predictive analytics for route optimization and accurate delivery estimates, predictive maintenance on fleet telematics to avoid breakdowns, and computer vision in the warehouse to improve picking accuracy and reduce mis-ships.
Education & Edtech
An edtech platform builds adaptive learning paths from student performance data and an AI tutoring assistant grounded through RAG on approved curriculum, with automated grading kept under human oversight and handled in a FERPA-aware way, raising completion rates without lowering academic integrity.
Custom AI versus off-the-shelf tools
Off-the-shelf AI tools are fast to switch on and fit narrow, common tasks. Custom AI development wins when the advantage comes from your own data, workflow and control. Here is the honest comparison.
| Factor | Off-the-shelf AI tools | Custom AI development with us |
|---|---|---|
| Use of your data | Limited; works mainly on generic or shared data | Built on your proprietary data for accuracy specific to you |
| Data control | Data often leaves your environment | Private deployment and US data residency possible |
| Workflow fit | Fixed to the vendor’s design | Shaped to your exact process and systems |
| Ownership | Subscription; you own nothing | You own the code, models and data |
| Cost shape | Lower upfront, recurring per-seat fees | Higher upfront, compounding advantage and control |
| Best for | Common, low-differentiation tasks | Core processes where AI is a competitive edge |
| Factor | In-house AI hire | Dedicated AI team with us |
|---|---|---|
| Time to a working team | Months of recruiting for scarce skills | Days to weeks from an existing bench |
| Cost per senior engineer | High and rising in the US market | A fraction, with comparable skill |
| Breadth of specialists | Limited by who you can hire locally | ML, NLP, vision, agents & MLOps on tap |
| Scaling up or down | Slow and costly either way | Flexible, on monthly terms |
| MLOps and maintenance | Additional headcount needed post-launch | Same team supports what it built |
Our AI development process
We follow a transparent, agile process so you see working results early and keep control of scope, cost and quality throughout the engagement.
Discovery & AI strategy
We map your goals, data and constraints and agree on the use cases worth building, with a costed roadmap and clear success metrics.
Data preparation
We assess, clean and structure your data into a reliable foundation, identifying gaps and addressing them before the build begins.
Prototyping
We build a proof of concept to validate accuracy and value before full investment, so you commit budget to what works.
Development & integration
We build the production system and connect it to your apps, platforms and existing tools through secure APIs.
Testing & responsible AI review
We check accuracy, bias, security and performance against agreed targets before any user sees the system.
Deployment & MLOps
We launch, monitor and retrain so the system stays accurate over time, operated by the same team that built it.
Governance answered in the contract, not just on a page
Data privacy & compliance
We encrypt data in transit and at rest, support US cloud data residency, minimize PII exposure and align with HIPAA, SOC 2 and CCPA where they apply.
IP ownership & confidentiality
NDAs and clear contracts assign full ownership of the code, models and data to you, with controlled access and a clean handover.
Governance & bias control
Role-based access controls, audit logging, data documentation and bias testing on decisions that affect people, so the system can stand up to internal and external review.
Monitoring & human oversight
Dashboards track model performance and data drift; for high-stakes decisions in lending, healthcare and hiring, a person stays in the loop with clear escalation.
Technologies we work with
Model-agnostic by design. We choose by accuracy, cost, privacy and whether you need private or on-premise deployment.
A trusted AI development company in the US
Proven track record
Building digital products since 2014 across three continents, including a US footprint and New York presence.
Recognition and clients
Recognised as a CIO Top App Development Company, trusted by Al Jazeera, the Manipal Group and the Confederation of Indian Industry.
Custom, not off-the-shelf
We build to your exact requirement instead of selling a template. You get a system shaped to your data, workflow and compliance needs.
Clear IP ownership
Full ownership of the code, models and data is written into the contract from day one, with a clean handover at the end.
Frequently asked questions
An AI development company designs and builds artificial intelligence software for businesses — including machine learning models, generative AI assistants, AI agents, computer vision and intelligent automation — and integrates them into existing systems. B2C Info Solutions covers the full path from AI strategy and data preparation through development, integration, deployment and ongoing MLOps.
Building an in-house team means recruiting scarce machine learning, data and MLOps talent, which is slow and expensive. A specialist partner gives you that capability immediately, ships a production system faster and stays accountable for outcomes while your team keeps focus on the core business.
Machine learning development builds models that predict or classify from your data — forecasting demand or detecting fraud. Generative AI uses large language models to create text, answers or content. Many real systems combine both, for example a predictive model feeding a generative assistant.
RAG, or retrieval augmented generation, grounds a large language model in your own approved data through a vector database, so answers are accurate and specific to your business instead of generic. If you want a generative AI assistant that reflects your documents, policies or catalog, you almost certainly need RAG.
We encrypt data, support US cloud data residency, minimize personally identifiable information and align with standards relevant to your industry such as HIPAA, SOC 2 and CCPA. You retain full ownership of your data and models throughout the engagement.
Yes, and we stay model-agnostic. We build on commercial APIs from providers such as OpenAI and Anthropic and on open-source models such as Llama and Mistral, choosing by accuracy, cost, privacy and whether you need private or on-premise hosting.
Most engagements begin within one to two weeks of an initial call. A proof of concept can often be delivered in a matter of weeks, with full production timelines depending on data readiness, integration depth and compliance requirements.
We operate it with MLOps — monitoring accuracy and data drift, retraining when accuracy moves — and support the system with the same engineers who built it, so it keeps working as data and conditions change.
Ready to build with a dependable AI development company in the USA?
Talk to our US team for a free consultation and a clear roadmap for your AI project.
