Best Custom Software Development Agencies For AI Projects

AI software development is no longer limited to research labs or tech giants.

More companies are building custom tools to solve business-specific problems using artificial intelligence, machine learning, and generative models. This often leads companies to weigh custom software development vs. in-house teams before kicking off an AI build.

Startups frequently turn to software development agencies offering custom software development to make those tools work. These agencies combine AI capabilities with software engineering, UX design, and integration support, building applications that fit a company’s systems, workflows, and technical constraints.

Custom-built solutions are created with flexibility, control, and long-term use. This matters when models must be adjusted for niche data or when teams want to embed AI into complex internal platforms.

In this guide, we’ll look at ten software development agencies that support AI projects across industries.

You’ll see what sets them apart, what services they offer, and what to evaluate before choosing a development partner. If you’re planning an AI project in 2025, this comparison will help you move forward with clarity.

‍

What is an AI Custom Software Development Agency?

‍

An AI custom software development agency designs and builds applications using artificial intelligence based on a client’s data, tools, and requirements. Instead of offering ready-made platforms, the agency creates software from scratch to fit each business's use case.

AI custom software development agencies manage the full development process.

That includes setting up data infrastructure, training models, writing backend logic, and connecting AI tools to internal workflows or customer-facing features. Their teams usually combine software developers, data scientists, infrastructure engineers, and product specialists.

The goal is to help companies turn AI into working features that support precise business needs without hiring an internal team, something often handled better by external partners, as covered in what does a custom software development agency do?.

Depending on the challenge, most AI projects cover areas like machine learning, natural language processing, or generative AI. Many of the agencies covered here follow principles outlined in why SaaS startups work with software development agencies to scale, especially when launching AI tools quickly.

‍

What Makes a Software Development Agency Great at AI Projects?

‍

Experience With Real-World AI Implementations (Not Just R&D)

AI research alone doesn’t prepare an agency to deliver software that works in production.

A strong AI software development company will show results from past projects, not theoretical prototypes. This includes building models that run inside real products, integrate with live systems, and respond to user behavior.

Experience here means more than launching a chatbot.

It could include developing fraud detection pipelines, embedding generative AI into mobile apps, or improving search accuracy using machine learning. Agencies that work with startups and mid-market companies often focus on measurable outcomes, such as reduced time-to-resolution, increased automation rates, or improved customer accuracy.

Ask for proof. If an agency doesn’t share working examples, likely, they haven’t solved challenges similar to yours.

‍

Cross-Skilled Teams: AI, Data, Infra, & UX Working Together

‍

Strong results come from teams that connect every layer of the stack. A reliable custom software development company won’t just assign a few data scientists and call it a day.

You need infrastructure engineers to handle scaling, software developers to manage backend logic, and UX designers to shape how outputs are used. This kind of collaboration is also critical in AI visual development, where interface design and model output must stay in sync.

This mix matters because AI doesn’t live in isolation.

A great model becomes useless if it slows the interface or breaks when traffic spikes. Cross-functional collaboration is what lets agencies deliver working software instead of brittle demos.

When evaluating a software development agency, ask about its internal team structure. A team that has launched full apps before, especially under tight timelines, will handle complexity better than one that operates in silos.

‍

Proven Delivery of Custom AI Tools (Not Pre-Built Platforms)

‍

Agencies that deliver strong results don’t just offer integrations with third-party tools. They build AI features tailored to specific data sources, use cases, and workflows. That means training models from scratch, running targeted tests, and iterating based on honest feedback.

Custom tools often include recommendation engines, automated insight generators, or internal copilots.

These projects require close collaboration across the entire development team, from model tuning to software testing.

What matters is ownership. If an agency can only install someone else’s model, it will quickly reach limitations. Look for partners who design, build, and support solutions they fully understand. That’s where lasting value comes from.

‍

Integration With Business Workflows & Existing Software

‍

AI software isn’t helpful if it operates in a vacuum.

A skilled software development company can integrate new models into current systems, such as a CRM, internal dashboard, or mobile app. Integration is where most projects fail.

Look for agencies that can explain how their solutions connect to existing platforms. That includes managing APIs, syncing data, securing endpoints, and building clean handoffs into daily operations.

The best custom software development partners ask about the tools your team already uses. That conversation shapes the design, reduces rework, and avoids surprises later on.

An application that runs well in your environment is more valuable than one that only performs in testing, which is one reason many teams prefer custom software over off-the-shelf platforms.

‍

Top Custom AI Software Development Agencies in 2025

‍

Below are ten agencies that work with artificial intelligence across industries.

Each offers full-service custom software development with AI integration. Some specialize in machine learning infrastructure, while others focus on building complete applications powered by generative models or natural language processing.

All firms listed have delivered client-facing tools or internal platforms, not just prototypes. You’ll find a range of industries, tech stacks, and collaboration styles. If you're just starting out, it helps to first understand which industries can benefit from AI development and align partners accordingly.

One of them brings a particularly strong mix of AI and no-code expertise for clients moving fast.

‍

1- NerdHeadz

‍

‍

NerdHeadz builds full-stack AI software, from early prototypes to production-ready platforms. They’re often brought in when startups need to deliver AI features fast, without giving up performance or user experience.

Clients rely on them to integrate LLMs, design backend logic, and launch tools that support search, automation, or customer-facing predictions.

Their strength is how tightly their teams work across AI, UX, and infrastructure. Unlike firms that bolt AI on top, NerdHeadz starts from the problem and works down to the data layer, choosing the right models, managing deployment, and delivering custom software that aligns with existing stacks.

That structure allows them to move quickly while solving challenges that typically slow down larger agencies. Their reputation has earned them a spot in NerdHeadz among the top 3 Bubble no-code agencies worldwide.

They’ve delivered internal copilots, AI-native onboarding flows, and embedded insights inside SaaS products, without requiring clients to staff an entire AI development team.

NerdHeadz also publish hands-on technical guides, like how to implement retrieval-augmented generation (RAG), for teams adopting generative AI.

Location: Global team with delivery centers in Latin America and Europe

Notable clients: Flusk, Early-stage SaaS startups

‍

2- LeewayHertz

‍

‍

LeewayHertz is a software development company with deep experience in enterprise-grade AI projects.

Their team builds machine learning systems, large language models (LLMs), and data-centric tools for established companies. They usually focus on integrating AI into high-volume platforms, such as customer service interfaces or predictive analytics engines.

What makes them notable is their combination of full-stack product development and AI infrastructure support. They offer everything from UI design and backend engineering to model deployment and performance tracking.

LeewayHertz is also active in blockchain and IoT projects, though AI-focused work remains a key part of their offering.

Location: San Francisco, USA

Notable clients: ESPN, Siemens, P&G

‍

3- InData Labs

‍

‍

InData Labs is an AI development company with a strong focus on data science and analytics.

Its work includes natural language understanding, facial recognition, and demand forecasting. Companies often choose InData Labs because they already have data but need help turning it into working software.

Their team includes data engineers, machine learning specialists, and software developers. Projects constantly involve designing custom recommendation systems, optimizing search results, or building computer vision pipelines.

While they serve multiple industries, their experience with AI systems in media and e-commerce gives them a strong foundation in high-volume processing and personalization logic.

Location: Nicosia, Cyprus

Notable clients: Wargaming.net, Captiv8, Flo

‍

4- Markovate

‍

‍

Markovate blends AI software development services with product strategy and cross-platform engineering. It usually partners with early-stage ventures to build MVPs with machine learning components, such as fraud detection, sentiment analysis, or AI-enhanced mobile features.

Their strength lies in speed and flexibility.

The agency covers both cloud-native deployment and edge device integrations, depending on the product’s needs. Their developers collaborate with clients to define clear outcomes, iterate quickly, and handle full application delivery.

For companies seeking a balance between structure and adaptability, Markovate offers a reliable model.

Location: Toronto, Canada

Notable clients: startups in healthtech, fintech, and mobility

‍

5- ScienceSoft

‍

‍

ScienceSoft offers full-scale custom software development services, with growing capabilities in artificial intelligence. Their AI work often supports enterprise workflows, from sales forecasting and pricing optimization to healthcare diagnostics and customer support automation.

The agency focuses on end-to-end delivery. Their focus on traceability aligns well with industries exploring what is agentic AIand other forms of autonomous intelligence.

Its teams handle everything from data preparation and model training to system integration and software testing. ScienceSoft also emphasizes compliance-heavy industries, where audit trails and explainable AI are critical.

It offers a mature engagement model for companies seeking structured delivery with a strong emphasis on documentation and reliability.

Location: McKinney, Texas, USA

Notable clients: IBM, Walmart, Nestle

6- ELEKS

‍

‍

ELEKS is a software development company with strong technical depth and global delivery capabilities. Their AI software development projects span computer vision, robotic process automation, and data analytics.

Most of their AI work supports logistics, fintech, and cybersecurity use cases.

Their teams include software engineers, AI researchers, and system architects who collaborate across time zones. They focus on creating scalable software solutions that can evolve with complex product needs.

ELEKS is also active in innovation labs and supports companies that need help mapping business requirements into working technical models.

Location: Tallinn, Estonia

Notable clients: Aramex, Autodesk, ESET

7- Vention

‍

‍

Vention supports fast-growing tech companies by providing outsourced development teams with AI experience. Their AI work often includes predictive features inside mobile and web apps, such as usage-based recommendations, risk scoring, and LLM-powered user support.

Vention stands out for its flexible team models.

Depending on budget and scope, companies can start with staff augmentation or shift to full product development. Their engineers understand how to integrate artificial intelligence into real-time platforms without slowing the development timeline.

For startups moving quickly, Vention offers both speed and engineering depth.

Location: New York, USA (with teams across Eastern Europe and LATAM)

Notable clients: ClassPass, Dialogue, Freshly

8- Altar.io

‍

‍

Altar.io is a product-focused software development agency that often works with founders and innovation teams.

Their AI software development projects typically involve early discovery, data analysis, and prototype delivery, especially for fintech, edtech, and B2B platforms looking to integrate machine learning into their products.

Their team includes product strategists, full-stack engineers, and data scientists.

They’re known for shaping early-stage ideas into launch-ready software. When artificial intelligence is part of the roadmap, Altar.io helps companies scope the use case, build the infrastructure, and align development timelines with real business goals.

Location: Lisbon, Portugal

Notable clients: Siemens, Dreamshaper, Blockchain startups

‍

9- MojoTech

‍

‍

MojoTech focuses on custom software development for companies undergoing digital transformation. Their AI work often supports health tech and enterprise applications, helping clients automate manual tasks, extract value from internal datasets, or deliver predictive functionality to customers.

They manage complete application builds and offer post-launch maintenance services.

The agency brings together software engineers, product managers, and infrastructure specialists to handle both frontend delivery and backend complexity.

MojoTech is a good fit for companies with long-term product plans that involve integrating AI features in phases. For companies working in healthcare or insurance, their use of predictive features echoes trends in how retailers use NLP to make retail decisions.

Location: Providence, Rhode Island, USA

Notable clients: Aetna, Blue Cross Blue Shield, United Way

‍

10- Itransition

‍

‍

Itransition is one of the larger software development firms on this list, offering enterprise-scale AI integration alongside its broader development services.

It works across industries, including e-commerce, supply chain, and finance, developing tools that support fraud detection, content classification, and customer service automation.

Their AI capabilities include model deployment, data preprocessing, and API-driven integrations. Itransition is often selected for projects that require a high degree of scalability or formal documentation.

With delivery hubs across Eastern Europe and Latin America, they provide consistent execution across complex software projects.

Location: Denver, USA (with global engineering teams)

Notable clients: Adidas, Toyota, PayPal

‍

How to Choose an AI-Focused Software Development Partner

‍

Technical Vetting: Data Infrastructure, Model Deployment, MLOps

‍

Before signing any contract, review how the agency handles technical architecture.

AI software development isn’t just about building a model, it depends on how data moves, where it’s stored, and how outputs are maintained after launch. This vetting stage is also where teams evaluate alignment with software development lifecycle (SDLC) best practices.

A capable development team should explain their process for preparing datasets, setting up pipelines, training and validating models, and monitoring them post-deployment. That includes documentation, testing, rollback plans, and performance tracking.

Without this foundation, even a good model will break under pressure. These are the kinds of questions every business should ask software development agencies before committing.

Ask for examples of how they’ve deployed machine learning models before, especially in high-usage platforms. They may not be ready to support production AI if they struggle to explain their infrastructure decisions or can’t walk you through a standard MLOps workflow.

‍

Business Alignment: Roadmapping, Timelines, Collaboration Models

‍

Strong technical skills don’t guarantee success.

The best custom software development companies align their work with your product roadmap and delivery expectations. That includes clear phases, regular checkpoints, and transparent scope management.

Ask how they handle scope changes, who leads backlog grooming, and what kind of documentation they provide. Look for signs they’ve delivered enterprise software under real timelines, not just lab experiments or internal demos.

Team structure matters here, too. Can they provide product managers, or will they expect direction from your side?

While keeping delivery on track, agencies that guide clients through business decisions tend to deliver higher-quality software solutions without creating management friction.

‍

Questions to Ask Before Signing a Contract

‍

Vetting a software development partner goes beyond technical skills. You need to understand how they work, what risks you’re taking on, and how they’ll respond when things change.

A few key questions to clarify the software development process:

• Who owns the IP, models, and codebase?
• What happens if the project needs to pause or change direction?
• Will you receive full documentation for models and infrastructure?
• How do they handle communication during emergencies or missed deadlines?

The more detailed their answers, the more prepared they are for real projects. Avoid firms that offer vague answers or try to skip this stage; those gaps will show up when the stakes are higher.

‍

Red Flags to Watch in AI Service Proposals

‍

Even strong pitches can hide weak execution.

If an agency promises results without asking about your data quality, usage environment, or target workflows, that’s a red flag. AI software isn’t plug-and-play, it needs context to work.

Avoid firms that claim they’ll deliver full functionality without model testing or iterative delivery. Also, be cautious if the proposal doesn’t include post-launch maintenance or performance tracking. That usually means they don’t expect to be around when problems appear.

Overuse of buzzwords like “revolutionary,” “seamless,” or “cutting-edge” can also signal a lack of depth.

Look for agencies that speak clearly, map ideas to outcomes, and focus on solving real business problems, not selling hype. Qualities outlined in our guide on how to choose the custom right software development agency.

To avoid mismatches, some teams start with a smaller scope, like an MVP or prototype, before committing to full delivery.

‍

What Services Do Custom AI Software Agencies Provide?

‍

AI Strategy & Use Case Discovery

‍

Most companies don’t start with code, they start with a problem.

AI-focused software development firms often guide clients through discovery sessions to define what artificial intelligence can (and can’t) solve. These sessions translate broad ideas into viable projects. These services mirror those listed in steps to integrate deep learning into SaaS business processes, especially around post-deployment training.

The agency’s job is to evaluate your data, clarify goals, and assess if AI is the right fit. That might lead to a roadmap, feature shortlist, or prototype strategy.

Sometimes, it may reveal that traditional software is a better option.

Use case discovery is especially valuable for teams without internal AI leadership. Agencies bring technical context, past examples, and delivery experience to shape smarter decisions before development begins.

‍

Model Selection, Training, & Testing

‍

Once a problem is defined, agencies handle the technical heavy lifting.

That starts with selecting or designing the right model, whether a pretrained transformer or a custom architecture built from smaller components.

After choosing the model, the software development team prepares training data, tests assumptions, and tunes performance against real targets. They evaluate how well the model performs under different edge cases and user patterns.

Testing doesn’t stop at accuracy.

It includes speed, compatibility with other software, and resilience to low-quality inputs. Agencies that take this stage seriously can build custom software that holds up under real usage, not just lab tests.

‍

Data Cleaning, Annotation, & Labeling Support

‍

High-quality models require high-quality data.

That’s why many agencies offer services to help clients clean, structure, and label their information before training begins. This stage usually determines the project's performance.

Support here may include building data pipelines, tagging text for sentiment, or reviewing image datasets for consistency. The goal is to produce inputs that match the model’s expectations and align with business outcomes.

Custom AI development firms may also advise on tooling, such as choosing between manual annotation, automation, or third-party platforms. Teams that skip this stage often face longer timelines or underperforming results.

‍

Full Application Buildout With AI Integration

‍

Some agencies stop at model delivery.

The better ones take that model and embed it directly into full applications. That includes writing the backend logic, shaping the frontend experience, and managing the connections between your AI tool and the rest of your stack.

This stage transforms code into usable software. It may involve building mobile apps, custom dashboards, web portals, or internal platforms, each designed to expose the model intuitively and reliably.

Agencies with strong software development experience treat AI as just one system layer. That means cleaner UX, better security, and easier iteration after launch.

‍

Post-Deployment Monitoring & Model Tuning

‍

AI software development doesn’t end with deployment.

Models drift. Inputs change. Outcomes degrade.

That’s why agencies often stay involved after launch to monitor system performance and refine outputs. Agencies that invest in monitoring also help prevent accuracy drift, an issue discussed in what is retrieval augmented generation (RAG)?.

Post-deployment work includes logging results, measuring model accuracy over time, adjusting thresholds, and updating datasets. It also means adapting the model when business requirements grow, without rebuilding from scratch.

Some agencies automate this feedback loop, while others provide manual audits or scheduled reviews.

Either way, ongoing maintenance separates functioning AI systems from broken ones. If a firm doesn’t offer model tuning after delivery, that’s a red flag for long-term reliability.

‍

When to Hire an AI Software Development Agency vs In-House

‍

Budget, Speed, and Access to Rare Skills

‍

Hiring an AI software development agency makes sense when timelines are tight and internal hiring is slow or expensive. Top engineers with machine learning experience are in high demand, and full-time hires often require long ramp-up times, equity, and specialized onboarding.

Agencies bring experienced development teams with the tools and structure already in place. This cuts time-to-delivery, especially when building custom software for niche use cases.

Companies avoid the overhead of managing payroll, recruiting, or internal tooling from scratch.

You also gain access to rare technical expertise, such as infrastructure engineers who’ve deployed LLMs in production, or data scientists who’ve tuned models in sensitive conditions. In most early-stage and mid-market cases, that mix is complex to assemble internally without blowing up the budget.

‍

When You Need to Experiment With Ideas Quickly

‍

Some projects don’t need long-term AI infrastructure; they need answers fast.

If your team wants to validate a feature, build a prototype, or explore what artificial intelligence can do with your data, agencies move faster than hiring internally.

An external development company can design an MVP, test an algorithm, and ship a working demo in weeks. You can assess outcomes and adjust without committing to permanent hires or architecture decisions. This flexibility is especially valuable when ideas are still fluid during product discovery.

Agencies used to short cycles and cross-functional work can ship faster without sacrificing quality.

If you’re trying to move from concept to a working app before the quarter ends, this model fits better than a full hiring push.

‍

Long-Term Roadmaps vs Project-Based Delivery

‍

For ongoing AI development, the right model depends on your roadmap.

If your product relies on proprietary models, in-house teams may make more sense in the long term. However, project-based delivery is faster and easier to manage for specific tools or well-defined features.

Custom software development agencies shine on focused timelines with clear scope. They help you build once, launch cleanly, and scale later if needed. Some teams eventually bring work in-house after the initial version ships, using the agency’s code, documentation, and architecture as a foundation.

This structure gives flexibility without sacrificing ownership.

It’s especially effective when internal bandwidth is stretched or AI isn’t your company’s primary focus. In that case, building with an agency first, and hiring later, creates fewer delays and better handoff options.

‍

Conclusion

‍

Building software with artificial intelligence brings new possibilities, but also more complexity.

From model selection to data handling and integration, success depends on working with people who understand the entire software development process, not just AI theory.

The agencies listed above all bring something valuable. Some focus on scale, others on speed, and a few specialize in niche use cases. But when companies want to move quickly without sacrificing flexibility, NerdHeadz stands out.

Our team works across generative AI, machine learning, and real-world application delivery. We collaborate with SaaS startups, innovation teams, and founders who need working software, not slides or mockups.

From strategy to deployment, we help teams with custom software development services.

If you’re planning an AI project and need software development services from people who’ve done it before, without the red tape, get in touch. We’d be glad to learn more and help you move forward.

Talk to NerdHeadz about your AI software project.