AI-augmented software development services

Innowise builds AI into your engineering workflows and establishes metrics and review processes from the outset. Instead of relying on separate tools, you get an integrated approach that saves time and reduces costs.

50%

faster delivery and modernization timelines

30%

reduction in engineering and operational costs

Up to 5x

increase in developer productivity

Innowise builds AI into your engineering workflows and establishes metrics and review processes from the outset. Instead of relying on separate tools, you get an integrated approach that saves time and reduces costs.

50%

faster delivery and modernization timelines

30%

reduction in engineering and operational costs

Up to 5x

increase in developer productivity

Approach

Services

Portfolio

Outcomes

Consulting

Why us

Our approach to AI-augmented development

Innowise helps turn AI tools into a force multiplier for your engineering team. By automating routine work, your developers have more space to focus on complex problem-solving and keep human expertise in the driver’s seat.

Human expertise augmentation

We delegate repetitive work to AI: boilerplate, dependency mapping, and draft documentation. It frees your team to focus on tasks where human expertise matters most.

Unchanged workflows

We add AI to the IDEs, repositories, and CI/CD pipelines your team runs. Your developers keep working the way they’re used to.

Focus on outcomes

Our AI-augmented development services start by defining baseline metrics. We use them to measure the efficiency of AI rollout as we proceed.

Collaboration

Our engineers pair with yours, document decisions, and run sessions so your team can maintain and extend the AI workflows once we’re gone.

No vendor lock-in

We build with open standards and models you can swap without rewriting your systems. If you change AI providers or pricing, the roadmap remains intact.

Security & compliance

AI tools are scoped to your environment and data policies. We don’t pipe your codebase through third-party services, and we document integrations for the security team.

AI-augmented development services we offer

Code rebuild

App modernization

Testing & QA

DevOps and CI/CD

SDLC management

Procurement & integration

AI agent development

AI-driven code rebuild

When a task is to rebuild legacy systems into modern architectures, we use AI to take on the repetitive parts of refactoring and migration: syntax conversion, dependency updates, and structural changes.

Developer embedding AI into codebase, merging machine learning logic with software workflows

Application modernization

We run AI-augmented workflows across analysis, code conversion, and testing to compress modernization timelines. The systems move from legacy state to production-ready faster than with a fully manual rebuild, while validation keeps them stable.

Software engineer reviewing source code on a laptop in a technology-driven environment

AI-augmented testing & QA

Our team implements AI to help you generate test cases, surface edge cases that manual testing can miss, and grow coverage across your codebase. This way, you catch more defects earlier in the cycle without expanding your QA team.

Interacting with a live analytics interface to monitor workflow progress and efficiency

AI-augmented DevOps & CI/CD

We configure automatic code reviews in your CI/CD pipelines and implement AI-augmented observability for deployments. The releases are faster, with fewer issues reaching production. Your team gets more time to build instead of fixing problems.

DevOps engineers automate the CI/CD lifecycle, visualizing code integration and deployment in a single loop.

AI-first SDLC management

Your AI-augmented development team can rely on AI tools at every phase: planning, development, testing, and ongoing maintenance. Oversight and reporting are built in from start to finish. Your delivery is consistent across sprints.

Technical experts consulting on system diagnostics and business continuity in a mission-critical data environment

AI tools procurement & integration

We manage the full process from tool selection and licensing terms to compliance review. Then we handle the technical work of securely integrating new AI tools into your existing environment. Your processes remain undisrupted.

AI as the digital engine driving smart, adaptive experiences in metaverse ecosystems.

Custom AI agent development

We design and build AI agents for multi-step engineering workflows, such as code review triage, deployment checks, or incident routing, so your team spends less time on coordination and more time on engineering itself.

Software engineer integrating ML-driven virtual avatars into enterprise systems for advanced user interaction

AI-driven code rebuild

When a task is to rebuild legacy systems into modern architectures, we use AI to take on the repetitive parts of refactoring and migration: syntax conversion, dependency updates, and structural changes.

Developer embedding AI into codebase, merging machine learning logic with software workflows

Application modernization

We run AI-augmented workflows across analysis, code conversion, and testing to compress modernization timelines. The systems move from legacy state to production-ready faster than with a fully manual rebuild, while validation keeps them stable.

Software engineer reviewing source code on a laptop in a technology-driven environment

AI-augmented testing & QA

Our team implements AI to help you generate test cases, surface edge cases that manual testing can miss, and grow coverage across your codebase. This way, you catch more defects earlier in the cycle without expanding your QA team.

Interacting with a live analytics interface to monitor workflow progress and efficiency

AI-augmented DevOps & CI/CD

We configure automatic code reviews in your CI/CD pipelines and implement AI-augmented observability for deployments. The releases are faster, with fewer issues reaching production. Your team gets more time to build instead of fixing problems.

DevOps engineers automate the CI/CD lifecycle, visualizing code integration and deployment in a single loop.

AI-first SDLC management

Your AI-augmented development team can rely on AI tools at every phase: planning, development, testing, and ongoing maintenance. Oversight and reporting are built in from start to finish. Your delivery is consistent across sprints.

Technical experts consulting on system diagnostics and business continuity in a mission-critical data environment

AI tools procurement & integration

We manage the full process from tool selection and licensing terms to compliance review. Then we handle the technical work of securely integrating new AI tools into your existing environment. Your processes remain undisrupted.

AI as the digital engine driving smart, adaptive experiences in metaverse ecosystems.

Custom AI agent development

We design and build AI agents for multi-step engineering workflows, such as code review triage, deployment checks, or incident routing, so your team spends less time on coordination and more time on engineering itself.

Software engineer integrating ML-driven virtual avatars into enterprise systems for advanced user interaction

How we deliver in practice

Access the gains of AI-augmented development

Business outcomes

01/03

67% faster code review

Adopting AI tools helps teams review code faster by flagging issues, surfacing context, and highlighting risky changes before a reviewer starts. Reviewers can focus on what’s important rather than what’s obvious.

02/03

60 min a day saved

Teams free up 40–60 minutes per day, since AI clears repetitive tasks. The quality isn’t compromised because it’s measured against the same QA bar your team holds code to. Human efforts can be redirected to more complex tasks.

03/03

Visible ROI in Q1

Companies report positive ROI by the end of the first quarter if even 10-11% productivity gains are achieved. 88% of leaders are already witnessing ROI from their investments in AI.

01

67% faster code review

02

60 min a day saved

03

Visible ROI in Q1

Key business challenges we solve

Chaotic AI adoption

Teams pick up AI tools per project, with no shared process behind them. We put structure and governance in place so adoption follows a plan, and we track the results.

Low ROI visibility

To show leadership whether AI tools are paying for themselves, our team sets up tracking and reporting so the return is visible in clear numbers.

Underutilized tools

Licenses go half-used because teams don’t get the training to apply them. We close that gap so the tools you've already paid for earn their cost back.

Unpredictable engineering output

We put consistent workflows in place so output holds steady across teams and sprints. Delivery timelines and code quality don’t shift in projects.

Security and compliance risks

To avoid risks of AI-generated code and AI tools creating gaps in data handling and IP protection, we set safeguards and reviews based on your compliance requirements.

Legacy system limitations

Old systems slow teams down, but a full rebuild risks downtime. We modernize in stages, so operations keep running while the system underneath changes.

Our AI-augmented consulting services

Maturity assessment

Team enablement

Advisory & consulting

Agentic AI & PoC

Training

Strategy & governance

Rapid maturity assessment

Our team evaluates your engineering environment, current workflows, and team readiness across tools, processes, and skills to identify where AI will bring more impact. Then we translate those findings into a sequenced adoption roadmap.

Software engineer explaining source code to a team member during a collaborative coding session

AI-native team enablement

We embed AI into your engineering teams’ day-to-day work. Our experts train developers to apply AI-first practices to planning, coding, and review.

Software consultants coordinating on technical tasks for agile development and IT security management

Advisory & continuous consulting

Innowise stays engaged as a long-term advisor. Throughout the engagement, we evaluate new tools as they appear in the market, revisit your roadmap against results, and adjust strategy as your team's needs and AI capabilities change.

Executive team discussing software integration plans and analyzing progress data

Agentic AI & PoC development

Based on your workflows and data, we build and test AI agents and prototypes. This gives you an evidence-based view of what an agent can and can’t do. You validate the real-world value before you commit your budget to a full-scale build.

Intelligent system powering real-time business insights, automating pricing and product suggestions

Training & enablement

Our consultants train your teams in day-to-day AI workflows and security practices, with particular attention to where human review needs to stay in the loop. The oversight doesn't get lost as adoption scales.

Tech team reviewing UX concepts and mobile solutions at a product design session

Enterprise AI strategy and governance

Within consulting services, we design governance frameworks that address compliance, data handling, and IP protection. Then we tie each AI initiative back to specific business goals, so adoption decisions are traceable rather than ad hoc.

IT consultants conducting a project kickoff meeting in a modern glass office

Rapid maturity assessment

Our team evaluates your engineering environment, current workflows, and team readiness across tools, processes, and skills to identify where AI will bring more impact. Then we translate those findings into a sequenced adoption roadmap.

Software engineer explaining source code to a team member during a collaborative coding session

AI-native team enablement

We embed AI into your engineering teams’ day-to-day work. Our experts train developers to apply AI-first practices to planning, coding, and review.

Software consultants coordinating on technical tasks for agile development and IT security management

Advisory & continuous consulting

Innowise stays engaged as a long-term advisor. Throughout the engagement, we evaluate new tools as they appear in the market, revisit your roadmap against results, and adjust strategy as your team's needs and AI capabilities change.

Executive team discussing software integration plans and analyzing progress data

Agentic AI & PoC development

Based on your workflows and data, we build and test AI agents and prototypes. This gives you an evidence-based view of what an agent can and can’t do. You validate the real-world value before you commit your budget to a full-scale build.

Intelligent system powering real-time business insights, automating pricing and product suggestions

Training & enablement

Our consultants train your teams in day-to-day AI workflows and security practices, with particular attention to where human review needs to stay in the loop. The oversight doesn't get lost as adoption scales.

Tech team reviewing UX concepts and mobile solutions at a product design session

Enterprise AI strategy and governance

Within consulting services, we design governance frameworks that address compliance, data handling, and IP protection. Then we tie each AI initiative back to specific business goals, so adoption decisions are traceable rather than ad hoc.

IT consultants conducting a project kickoff meeting in a modern glass office

Why choose Innowise

Innowise has been in software development for more than 19 years. Over that time, we’ve been keeping abreast of technologies, learning and implementing them for our clients.

Project-tested methodology

Our approach comes from projects we’ve already delivered. Your project isn’t a beta test. It is guided by strategies that work reliably.

Scaling with your needs

Our talent pool is broad enough to take on projects from a single pilot to enterprise-wide rollout. You won’t need to switch partners as your needs grow.

Metrics-focused

We set clear baselines before we start and report against them. You’ll know if AI is paying off through data that shows how much time and cost you’re saving.

Knowledge transfer

We document decisions and train your team as we go. Your team remains independent of us as they have the skills and knowledge to manage these new workflows.

Governance and security

Our review processes and safeguards are built to match the compliance standards that your teams work under. Using AI won’t mean compromising on compliance.

Long-run partnership

We stay engaged beyond launch. We keep adjusting your AI software as your needs change and new technologies emerge.

Ship faster without growing the team

Let Innowise build AI into your workflows, so your team delivers more in less time

How we deliver results

Innowise’s strategy is to complete the projects in stages and measure results at each step. For AI-augmented development services, we follow this roadmap.

Discovery We look at your current workflows, tools, and team readiness. Then we set baseline metrics to measure progress against.

Pilot implementation We test AI-augmented workflows on a real project first, so you can see their impact in the context of actual work.

Scaling & integration After a workflow proves out, we roll it out across teams and build it into your CI/CD pipelines.

Optimization We bring in more advanced AI agents and refine the workflows in place as your systems and needs change.

What our customers think

All testimonials (55)

Innowise team acted professionally and proactively, tackling both strategic and urgent challenges equally well. They consistently brought best practices in responsible AI, e-commerce engines, and web technologies to the table.

Jonas Kullgren

CEO, Vidda Solutions AS

5.0

Read full review

See project details

Working with Innowise was exactly what we needed to bring our agentic web platform to life. They combined strong blockchain and AI expertise with excellent integration capabilities and contributed valuable connections, making them a reliable partner.

Sergei Gorovenko

Founder, HAIA

5.0

Read full review

See project details

Their team has consistently demonstrated a high level of expertise, professionalism, and dedication to our project. We have been very impressed with their ability to understand our needs, provide effective solutions, and meet our project timelines.

Joakim Rosén

Co-founder & CTO, Etals Core AB

5.0

Read full review

See project details

Technology stack

AI and LLM platforms

Azure OpenAI

Anthropic Claude

Google Gemini

Mistral

AI coding tools

GitHub Copilot

Cursor

Windsurf (formerly Codeium)

Tabnine

AI frameworks and orchestration

LangChain

LlamaIndex

Semantic Kernel

AutoGen

Machine learning frameworks

TensorFlow

PyTorch

scikit-learn

Data and vector databases

Pinecone

Weaviate

FAISS

Chroma

Elasticsearch

Cloud platforms

Microsoft Azure

Google Cloud Platform

DevOps and CI/CD

GitHub Actions

GitLab CI/CD

Jenkins

CircleCI

Azure DevOps

Containerization and orchestration

Docker

Helm

Infrastructure as code

Terraform

Pulumi

AWS CloudFormation

Monitoring and observability

Prometheus

Grafana

Datadog

ELK Stack

Security and governance

IAM

Vault

Microsoft Defender for Cloud

AWS Security Hub

Programming languages

TypeScript

Java

Go

APIs and integrations

REST

GraphQL

gRPC

AI and LLM platforms

Azure OpenAI

Anthropic Claude

Google Gemini

Mistral

AI coding tools

GitHub Copilot

Cursor

Windsurf (formerly Codeium)

Tabnine

AI frameworks and orchestration

LangChain

LlamaIndex

Semantic Kernel

AutoGen

Machine learning frameworks

TensorFlow

PyTorch

scikit-learn

Data and vector databases

Pinecone

Weaviate

FAISS

Chroma

Elasticsearch

Cloud platforms

Microsoft Azure

Google Cloud Platform

DevOps and CI/CD

GitHub Actions

GitLab CI/CD

Jenkins

CircleCI

Azure DevOps

Containerization and orchestration

Docker

Helm

Infrastructure as code

Terraform

Pulumi

AWS CloudFormation

Monitoring and observability

Prometheus

Grafana

Datadog

ELK Stack

Security and governance

IAM

Vault

Microsoft Defender for Cloud

AWS Security Hub

Programming languages

TypeScript

Java

Go

APIs and integrations

REST

GraphQL

gRPC

AI tools are strong now. To make adoption benefit your enterprise, you need to connect each tool to a workflow with a particular owner and a metric attached. Innowise builds that connection before your team deploys the first line of AI-generated code to production.

Head of AI Technical Expertise

FAQ

What is AI-augmented software development?

It is an engineering approach where AI automates certain tasks within software development, like code creation, testing, documentation, and refactoring. Engineers still retain authority over architecture, reviews, and decision-making.

What benefits can we expect from AI-augmented development?

AI-augmented development can lead to faster delivery timelines, lower development and operational costs, and higher output per engineer by taking over repetitive work that otherwise eats into schedules. It also supports broader test coverage and fewer defects reaching production, so software quality also improves.

How do you ensure data security and compliance?

AI-generated code and outputs go through the same checks as work produced by your team. For that, we build review and approval steps into every workflow. Before anything goes live, our engineers review tool selection, data handling, and access controls against your compliance.

How do you measure ROI from AI adoption?

We set baseline metrics before an AI workflow goes live, then track against those numbers throughout the engagement. You get reporting that shows the return in concrete terms, including time saved, defects caught, and costs reduced.

Can you work with our existing tech stack and teams?

Yes. We don’t ask you to switch platforms for the sake of AI adoption. Instead, we add AI into the tools, repositories, and pipelines your team uses. To make it blend, our engineers pair with yours throughout the project.

How long does it take to see results?

Our projects usually begin with a pilot. The results become evident within a couple of weeks. After the success of a pilot, the next step is to roll out the process at full scale.

Do you provide training for our internal teams?

Yes. We train your teams in prompt engineering, day-to-day AI workflows, and security practices. The focus is on where human review needs to stay in place. We also document decisions as we go, so your team can maintain and extend the workflows independently after our engagement ends.

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After examining your wants, needs, and expectations, our team will devise a project proposal with the scope of work, team size, time, and cost estimates.

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We’ll arrange a meeting with you to discuss the offer and nail down the details.

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