Andela

Helps organizations benchmark engineering teams’ AI capabilities, identify gaps, and prioritize improvements for stronger agentic adoption.

Helps engineering teams use AI agents, coordinate complex workflows, and build capability through real engineering work.

Builds practical AI and engineering expertise, prepares learners to develop production AI systems, and strengthens career prospects through hands-on training.

Modernizes technology and data, connects AI to trusted enterprise context, and delivers governed workflows teams can operate and scale.

Adds trained AI engineering capacity to help teams build, integrate, and scale AI systems in production.

Services that provide rapid augmentation of engineering teams with vetted developers and technical specialists for short- or long-term engagements, prioritizing fast ramp-up, specialized expertise, and risk-minimized trials.

Products: AI-native engineering talent

Consulting and custom AI development to embed machine learning into business workflows, including intelligent data extraction, scoring, and system integrations.

Products: Andela AI Solutions

Modernization of legacy applications and delivery infrastructure through migration, integration, cloud deployment, and automated release processes.

Products: Andela AI Solutions

Measures engineering teams’ AI proficiency and readiness, identifies capability gaps, and tracks skill development and workplace adoption to guide workforce development.

Products: Andela Assess

Instructor-led and applied training that helps organizations develop workforce capabilities in AI, engineering, cloud, data, and other technologies through role-specific curricula, projects, and readiness assessments.

Products: Andela AI Academy, Andela Learn agentic engineering programs

Andela Assess

Andela Assess helps enterprises understand how engineering teams use AI, measure agentic engineering readiness, and identify capability gaps. The assessment can examine repository inventory, pipelines, security policies, and team structure. Findings help shape learning paths, prioritize improvements, and measure capability growth and adoption over time.

• Benchmark Team AI Readiness
  Gives organizations a baseline view of engineering readiness, proficiency, and AI tool adoption to help clarify where teams stand.
• Measure Engineering AI Proficiency
  Shows how engineers are using AI in their work and provides a basis for benchmarking capability and readiness.
• Identify And Prioritize Capability Gaps
  Helps leaders see where skills or agentic practices need attention and decide which improvements to prioritize.
• Tailor Learning To Assessed Needs
  Connects assessment results to tailored learning so teams can focus development on observed capability needs.
• Measure Capability Growth
  Provides a way to compare capability after learning with the baseline and review growth across skills.
• Track Sustained Agentic Adoption
  Helps organizations review whether agentic practices carry into everyday work and monitor adoption signals over time.

Andela Learn agentic engineering programs

Andela Learn’s applied, assessment-led programs help enterprise engineering teams build the skills, judgment, and practices to use agentic AI in real engineering work. Adopt develops foundational individual agent use; Impact builds complex workflows and multi-agent orchestration; and Transform combines production solution delivery with hands-on team enablement. Learning is tailored to assessed skill gaps and can be delivered on Claude Code, GitHub Copilot, and OpenAI Codex.

Category: AI Training Services

• Advance Agentic Engineering Capability
  Teams can develop agentic capability step by step, moving from consistent individual use to multi-agent workflows and production solution delivery.
• Measure Growth And Sustained Adoption
  Baseline and exit assessments track capability development, while follow-up pulses help teams review whether new skills are carrying into everyday work.
• Apply Skills In Real Engineering Work
  Engineers practice agentic skills through realistic or live engineering work, including capstones, rather than relying only on classroom-style instruction.
• Coordinate Agents Across Complex Workflows
  Engineers learn to apply agents beyond basic assistance, coordinating multi-step work and agent interactions while maintaining human collaboration.
• Build Capability While Delivering Solutions
  Teams develop skills during delivery of a live AI system in a real codebase, with responsibility shifting as capability grows.
• Choose A Format That Fits
  Teams can select a short intensive or multi-week learning format, depending on the program level and its stated delivery structure.
• Train On Your AI Coding Tools
  Organizations can apply the learning programs to supported AI coding tools used by their engineering teams.

Andela AI Academy

Andela AI Academy offers cohort-based, hands-on AI training for technologists seeking to strengthen their applied AI and engineering skills. Learners can choose AI Foundations, covering AI-assisted coding and Kubernetes, or AI Engineering, covering LLM engineering, agentic AI, production AI, and AI leadership and strategy. The online AI engineering curriculum runs for 10 weeks with a stated commitment of 40 hours per week. Training includes practical projects, continuous assessment, and instruction on technologies used to build and operate AI systems.

Category: AI Training Services

• Develop Production-Focused AI Engineering Skills
  Learn to build and operate AI systems through topics that include reliable LLM applications, autonomous systems for complex workflows, scalable AI infrastructure, and AI strategy and adoption.
• Apply Skills To Real-World AI Projects
  Practice building AI systems throughout the curriculum and complete a capstone project intended to demonstrate enterprise AI skills in a portfolio.
• Build Strong AI And Software Foundations
  Develop skills in AI-assisted coding and Kubernetes to work with modern development workflows and the infrastructure used to support scalable software and AI.
• Measure And Validate Learning Progress
  Combine assessment and validation with curriculum design, practical projects, and peer mentoring as part of the learning process.
• Practice With Modern AI Technologies
  Learn with technologies named in the curriculum, spanning model platforms, vector databases, development tools, AI frameworks, evaluation and monitoring, and cloud and MLOps.
• Learn Through A Structured Online Cohort
  Follow a defined 10-week online curriculum with a stated 40-hour weekly commitment and a cohort learning format.
• Access Fortune 500 Job Opportunities
  The academy presents access to Fortune 500 job opportunities as a benefit for participants and states a potential earning increase of 20–40%.

Andela AI Solutions

Andela AI Solutions delivers the foundations and systems enterprises need to run AI in production. Andela modernizes legacy applications, platforms, developer tooling, and data; connects AI to trusted enterprise knowledge; and builds governed agentic workflows linked to business processes. The engagement is scoped around a defined outcome, with Andela responsible for staffing and delivery from design through implementation. Governance is built in, and delivery is designed so client teams can operate, extend, and build on the solution.

Category: AI Development Services

• Deliver Defined AI Outcomes
  Engage Andela to own delivery of a scoped AI outcome end to end, rather than only providing a roadmap or additional personnel for the client to direct.
• Modernize Systems For AI
  Move critical applications, platforms, workloads, and developer tooling toward AI-ready environments while addressing technical debt and improving scalability, maintainability, and performance.
• Prepare Trusted Data For AI
  Structure, migrate, optimize, and assess enterprise data so it can support modern AI workloads and provide a trusted foundation for AI systems.
• Connect AI To Enterprise Knowledge
  Ground AI systems in relevant business information by connecting enterprise sources and making their knowledge available through retrieval systems.
• Build Governed Agentic Workflows
  Transform manual or fragmented processes into workflows that connect agents with business systems and people, while retaining human oversight for approvals and escalations.
• Govern And Monitor Production AI
  Support reliable production deployment with evaluation, controls, testing, monitoring, and ongoing optimization for AI workflows and agents.
• Protect Enterprise Knowledge Access
  Apply permissions, auditability, and privacy-aware filtering to enterprise retrieval so access to business knowledge can be managed with security and compliance considerations.
• Improve Retrieval Quality
  Continuously assess and tune retrieval components to improve the relevance and performance of enterprise knowledge search in production.
• Align AI With Business Constraints
  Apply data governance practices and align models to business workflows and constraints, including specialized or regulated industry requirements.
• Equip Teams To Extend Solutions
  Prepare client teams to continue operating and developing delivered solutions, with assessment and applied learning available to build AI capability.

AI-native engineering talent

Andela provides AI-native engineers who can embed in enterprise teams to build, integrate, and scale AI systems in production. Engineers are trained and assessed on current AI tools and can add capacity for focused delivery, dedicated product, platform, or DevOps support, and larger programs. The talent network spans more than 135 countries and includes skills across artificial intelligence, application development, cloud and DevOps, and data engineering.

• Add AI-Native Engineering Capacity
  Bring engineers into existing teams to contribute to AI delivery, including work with Codex and OpenAI models.
• Deploy Trained And Assessed Engineers
  Access engineers whose AI capabilities are developed and evaluated through training, assessment, and practical project work.
• Build And Scale Production AI
  Add engineering skills for developing and operating AI systems beyond experimentation, including LLM, RAG, and agentic applications.
• Scale Engineering Support To Fit
  Choose focused individual capacity, dedicated teams, or larger-scale support according to delivery needs.
• Access Global Technical Talent
  Draw on a geographically diverse network of technologists with skills across AI and related technical disciplines.
• Evaluate Technical Capabilities
  Use technical assessments and live interviews to evaluate engineers’ capabilities, with continued validation in production.
• Match Engineers To Needed Skills
  Connect talent with opportunities using skills and work preferences, supported by AI and human sourcing.