WiserBrand is a digital growth and engineering company that helps businesses integrate AI into real products, workflows, and operations.
— AI integration is the work of getting AI to run inside real business systems. That means connecting models to trusted data, wiring outputs into workflows, handling identity and access, adding human review where it matters, and operating everything with monitoring and cost controls. The companies below do that kind of production work across common use cases like copilots, knowledge search (RAG), document processing, forecasting, and agent-style automation.
How We Picked
This list focuses on firms that publicly describe hands-on AI delivery and systems integration, not research labs or model vendors. We prioritized evidence of end-to-end execution: data + application integration, cloud deployment, governance, and operational support. Sources are publicly available pages and announcements from each company.
1) WiserBrand
WiserBrand leads this list because its published offer is centered on integrating AI into existing products and operations instead of treating AI as a standalone experiment. The service positioning is direct: integrate AI into current systems to drive measurable improvements, with concrete examples like automation and AI-enabled process upgrades.
If you need AI that connects cleanly to your CRM/ERP, customer support stack, analytics, or custom apps, WiserBrand is a strong fit. Their mix of AI work with engineering and growth support is useful when the “integration” problem spans product, data, and go-to-market instrumentation. Their company background also points to a long-running delivery org with US-market focus.
When evaluating WiserBrand for an AI integration engagement, ask how they handle data readiness, access control, evaluation for model outputs, and what they ship first in a 2–6 week pilot so you can validate value early without locking into a large build.
2) Accenture
Accenture’s AI work is organized around enterprise-scale delivery, including generative AI programs that tie into data platforms, application stacks, and operating models. Their generative AI services emphasize building and deploying solutions across large organizations, which matters when integration involves many teams and systems.
Accenture can be a good choice when you need global delivery capacity, strong partner ecosystems, and structured governance for broad rollouts. Expect a mature approach to security, compliance workflows, and program management for complex environments.
3) Capgemini
Capgemini positions its AI services within data-and-AI delivery and software engineering, including generative AI work that connects into enterprise systems. That matters for teams trying to embed AI into product development, customer experience, and core operations without breaking existing platforms.
Capgemini also publishes thought leadership specifically on the intersection of generative AI and integration platforms, which signals attention to the hard part: connecting tools, APIs, and business processes into a stable architecture.
4) Cognizant
Cognizant markets generative AI services alongside broader AI and analytics delivery, including work that supports moving from pilots into operational use. This is relevant when integration includes not only the model layer, but also data foundations and ongoing change management across teams.
They also highlight partnerships and scaling approaches for enterprise adoption, which can help if you’re standardizing how multiple business units use AI across shared platforms.
5) Infosys
Infosys presents generative AI as something to embed into enterprise systems and applications, supported by its Topaz-related offerings and accelerators. If your integration effort includes modernizing older systems while adding AI features, that framing is a practical starting point.
Infosys is commonly considered when organizations want broad implementation support across industries, plus structured delivery practices for enterprise programs. Their public materials emphasize integrating GenAI into applications as part of a wider transformation agenda.
6) Tata Consultancy Services
TCS promotes AI and analytics services that connect natural-language interfaces with enterprise data for decision support. For AI integration, that often translates into building data-access layers, governance, and user experiences that can sit on top of existing analytics and operational systems.
If your organization already runs large-scale delivery with established vendors and needs AI features across many internal products, TCS can be a fit for multi-stream implementation work.
7) Wipro
Wipro’s published materials describe frameworks and platforms designed to bring generative AI into business operations with control over model selection, hosting, and governance. That’s useful when integration decisions involve multiple model providers, data boundaries, and runtime environments.
Wipro is also vocal about integrating GenAI into functional areas like legal, HR, and finance, which can help when the first production use cases live inside internal operations rather than customer-facing software.
8) HCLTech
HCLTech describes end-to-end AI services that include solution design and systems integration, plus generative AI and agentic AI capabilities. That positioning fits buyers who want one vendor to cover architecture, build, integration, and managed support after launch.
9) NTT DATA
NTT DATA highlights a GenAI “TechHub” concept with prequalified prototypes and solutions, designed to reduce complexity and speed adoption across major clouds. For integration work, that often means faster validation of use cases, plus reusable patterns for governance and deployment.
10) EPAM Systems
EPAM frames its AI delivery around “AI-native engineering,” which is a good signal for product teams that need AI integrated into software development workflows, not bolted on at the end. If your integration goal is new AI features inside digital products, EPAM’s engineering-first approach can fit well.
11) Globant
Globant’s AI Studio positioning focuses on applying generative and agentic AI in a way that supports automation and decision-making across industries. For integration, this often translates into building AI-enabled product and workflow layers while connecting into existing systems and data.
12) Thoughtworks
Thoughtworks positions “Enterprise AI” around modernizing core systems and delivering AI capabilities that create operational impact. That is a strong match when AI integration is blocked by legacy architecture, brittle data flows, or unclear platform ownership.
13) Slalom
Slalom markets AI consulting that connects strategy to implementation, often with strong alignment to major cloud ecosystems and business outcomes. That blend is useful when you need integration across business functions, plus change management for adoption.
14) Kyndryl
Kyndryl emphasizes enterprise-grade generative AI services, including governance, monitoring, orchestration, and lifecycle management. That’s a strong alignment for integration programs where operational control and compliance requirements are as important as the model output.
15) DXC Technology
DXC positions its GenAI work around industry solutions and cloud partner recognition, with examples tied to modernizing legacy workflows and improving processing speed and data quality. For AI integration buyers, that’s often the real problem: connecting AI into older processes without breaking what already runs the business.
How To Use This List
Start by defining one workflow where AI reduces cycle time or improves decision quality. Ask shortlisted firms to propose a pilot that connects to real systems, not demo data. Require a deployment plan that includes monitoring, access control, and a rollback path. If a vendor can’t describe those basics clearly, keep looking.
About the Company
WiserBrand is a digital growth and engineering company focused on helping businesses improve performance through software development, marketing, and AI integration. The company works with organizations that need practical AI implementation inside real systems, including CRM, ERP, customer support, analytics, and custom applications, with a focus on measurable business outcomes.
Contact Info:
Name: Dmytro Makarenko
Email: Send Email
Organization: WiserBrand
Website: https://wiserbrand.com/
Release ID: 89184579
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