Ciklum
AI-powered experience engineering for digital enterprises with 25+ AI products in production
Founded 2002 | London, UK | 3,000+ employees
custom-mlgenerative-aimlopsdata-engineeringai-strategystaff-aug
What is Ciklum?
Ciklum is an AI-powered experience engineering company founded in 2002 and headquartered in London, UK, with 3,000+ engineers across 19 global locations. The firm brings 25+ years of product and AI excellence to FinTech, Retail, Healthcare, and Hi-Tech — from foundational AI and agentic automation to accelerated software engineering. Ciklum reports 25+ AI products already in production and 10+ years of AI expertise, and serves enterprise clients globally.
Ciklum was founded in 2002 and is headquartered in London, UK. The firm employs 3,000+ people and works primarily with clients in Financial Services, Retail & E-commerce, Healthcare & Life Sciences, Media & Entertainment, SaaS & Technology sectors. Its primary differentiator is: 25+ AI products in production combined with 3,000+ global engineers — enterprise AI scale without the big-four overhead.
Ciklum tech stack and services
PythonTensorFlowPyTorchAWSAzureGCPKubernetesApache Spark
| Service area |
|---|
| Custom ML Development |
| Generative AI |
| MLOps & Deployment |
| Data Engineering |
| AI Strategy |
| Staff Augmentation |
Ciklum use cases
Short answer: Ciklum is best suited for FinTech, Retail, Healthcare enterprises — AI product engineering at scale.
| Use case |
|---|
| Enterprise FinTech AI product build with agentic automation and fraud detection ML |
| Retail personalisation AI platform with product recommendation and pricing optimisation |
| Healthcare patient pathway ML for hospital system across multiple regional sites |
| Digital product engineering with AI features for Hi-Tech enterprise client |
| Staff augmentation of large internal AI team with specialist ML and MLOps engineers |
Ciklum pricing
Short answer: Ciklum uses a dedicated team, t&m, fixed project pricing approach. Minimum engagement starts at $75K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
| Fixed project | From $75K | Well-defined scope |
Ciklum does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Ciklum pros and cons
| Advantages | Things to consider |
|---|---|
| +25+ AI products verified in production — strong proof of delivery, not just design | -$75K minimum limits accessibility for smaller ML projects |
| +Global 19-location delivery network for enterprise programmes requiring regional presence | -Large-firm delivery model — less agile and responsive than boutiques for fast-iteration work |
| +FinTech, Retail, and Healthcare vertical depth with domain-specific ML capabilities | -Ukraine and Eastern Europe delivery mix carries geopolitical risk for some enterprise procurement teams |
| +Agentic AI and automation practice alongside core ML development | |
| +London HQ provides natural alignment with GDPR and EU AI regulatory frameworks |
Ciklum vs alternatives
How Ciklum compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market teams, specialist CV/time-series/LLM delivery. | Boutique ML depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ML services market | 4.9 | Full comparison |
| LeewayHertz | Businesses, GenAI/LLM integration plus custom ML. | Among the earliest boutique firms to build a structured GenAI delivery framework — deep LLM orchestration and RAG pipeline experience | 4.1 | Full comparison |
| Scopic | Companies needing genuinely custom ML architectures. | Engineers custom ML architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline | 4.6 | Full comparison |
| InData Labs | Complex ML problems, deep data-science expertise. | Boutique firm with a track record of solving atypical, high-complexity ML problems that generalist shops decline or under-deliver on | 4.6 | Full comparison |
| DATAFOREST | Mid-market companies, full ML pipeline ownership. | Structured MLaaS delivery model — one team owns data engineering, model development, and post-deployment monitoring end-to-end | 4.5 | Full comparison |
| Forte Group | Regulated finance/insurance firms, audit-ready ML governance. | ML delivery built for regulated environments — model risk governance, audit trails, and compliance-aligned architecture are built in, not bolted on | 4.5 | Full comparison |
| RTS Labs | High-growth US companies, production-accountable ML partner. | Small by choice, senior by design — every project is staffed with senior practitioners accountable for post-launch performance, not just the plan | 4.5 | Full comparison |
| Quantiphi | Enterprises, cloud-native ML, top-tier AWS/GCP credentials. | AWS Premier and four-time Google Cloud Partner of the Year — the highest independently verified cloud ML credentials in the market | 4.4 | Full comparison |
| N-iX | EU/US enterprises, large dedicated teams, competitive rates. | Scale and depth in one package — 2,000+ engineers with a mature ML practice and competitive EU delivery rates | 4.4 | Full comparison |
| Miquido | Product companies, ML/GenAI embedded, fast time-to-demo. | GenAI and mobile ML integration in one team — a rare combination for companies building AI-native products for end users | 4.4 | Full comparison |
| Algoscale | Fortune 500 and growth-stage companies, cloud data lakehouse... | 100+ production ML deployments on AWS, Azure, and Snowflake — proven at enterprise scale with multiple cloud stacks | 4.3 | Full comparison |
| STX Next | Python-stack product companies, tightly integrated ML plus MLOps. | Europe's largest Python shop — ML is embedded in full-stack Python systems with MLOps, not delivered as an isolated model | 4.3 | Full comparison |
| Intellias | Enterprises, AWS-native ML, validated CV/NLP/RAG results. | AWS AI Services Competency with verified production benchmarks — 10x TCO reduction in aerial imagery and sub-8-second NLP query latency | 4.3 | Full comparison |
| ScienceSoft | Healthcare/finance orgs, HIPAA/PCI-DSS/SOC2-compliant ML. | Over 35 years of regulated IT delivery — compliance-aligned ML architecture is a core competency, not an add-on | 4.2 | Full comparison |
| Simform | Manufacturing/logistics enterprises, cloud-native ML plus IoT. | AWS Premier Partner specialising in connecting physical IoT sensor data to cloud-based ML models for predictive maintenance | 4.2 | Full comparison |
| Oxagile | Healthcare/media/retail enterprises, cost-effective Eastern European ML. | Strong connected-care and healthcare AI track record combined with 40–60% cost advantage versus US equivalents | 4.2 | Full comparison |
| Softeq | Companies building AI for edge and embedded hardware. | Hardware-to-cloud ML engineering — a rare full-stack capability covering embedded device AI through cloud model serving | 4.1 | Full comparison |
| Aimprosoft | SMBs, AI consulting and custom ML at accessible... | Full-cycle AI delivery from consulting through implementation, optimised for SMB budgets and timelines | 4.1 | Full comparison |
| Uvik Software | Teams with an existing ML codebase, embedded senior... | Senior-only ML engineer staffing — embedded in your stack, working in your tools, without agency overhead | 4.1 | Full comparison |
| Iflexion | ML newcomers, AI strategy and scoping first. | Consulting-first model ensures the ML problem is correctly defined before engineering investment begins | 4.0 | Full comparison |
| Itransition | EU-operating enterprises, GDPR/EU AI Act-compliant ML. | EU regulatory compliance depth for ML — GDPR-aligned data architecture and EU AI Act readiness built into delivery | 4.0 | Full comparison |
| DataToBiz | Startups taking an ML idea to market-ready delivery. | Product-oriented ML delivery — combines AI strategy with full-cycle engineering to produce launchable products, not just models | 4.0 | Full comparison |
| BairesDev | Enterprises and scale-ups, fast teams, US time-zone aligned. | Latin American engineering delivery with US time-zone alignment — faster team ramp than Asian offshore with significant rate advantage versus US onshore | 4.0 | Full comparison |
| Andersen Lab | Enterprises, large-scale ML, Fortune-500 references, EU footprint. | Named client references including Siemens, S&P Global, and Ryanair — enterprise ML track record at the highest scale | 4.0 | Full comparison |
| Intuz | SMBs, US-headquartered AI/ML at accessible rates. | 1,700+ delivered projects for SMBs — the broadest SMB ML delivery track record in this list | 3.9 | Full comparison |
| Tredence | Fortune 500 enterprises, AI analytics and supply-chain ML. | Large specialised analytics and AI firm — enterprise supply chain ML and CX analytics depth with Fortune 500 client delivery track record | 3.9 | Full comparison |
| Codiant | Budget-conscious orgs, end-to-end ML delivery. | Cost-efficient end-to-end ML delivery covering all phases — discovery, build, integration, and optimisation — in a single engagement | 3.9 | Full comparison |
| GlobalLogic (Hitachi) | Global enterprises, massive-scale MLOps, Hitachi-backed. | Hitachi Group backing with 27,000 engineers — the scale and compliance posture of a major industrial conglomerate applied to enterprise ML | 3.9 | Full comparison |
| EPAM Systems | Global enterprises, complex AI products, governance at scale. | AI-native engineering practice at 50,000-person scale — the broadest talent pool and delivery capacity of any firm on this list | 3.8 | Full comparison |
| Cognizant | Fortune 500 enterprises, multi-year AI transformation programmes. | One of the world's largest AI & Analytics practices — Fortune 500 industry vertical depth and compliance credentials at 350,000-person delivery scale | 3.8 | Full comparison |
| Accenture | Global enterprises, governed GenAI and agentic AI at... | Accenture's global AI practice applies consulting strategy, industry domain expertise, and engineering delivery at 700,000-person scale — designed exclusively for enterprise | 3.8 | Full comparison |
| DataRobot | Enterprise data-science teams, governed AutoML platform. | Platform-driven ML — DataRobot's AutoML engine and MLOps governance layer enable internal data science teams to build and manage models at scale without per-project custom development | 3.8 | Full comparison |
Ciklum FAQ
What is Ciklum?
Ciklum is an AI-powered experience engineering company founded in 2002 and headquartered in London, UK, with 3,000+ engineers across 19 global locations. The firm brings 25+ years of product and AI excellence to FinTech, Retail, Healthcare, and Hi-Tech — from foundational AI and agentic automation to accelerated software engineering. Ciklum reports 25+ AI products already in production and 10+ years of AI expertise, and serves enterprise clients globally.
How much does Ciklum charge?
Ciklum uses dedicated team, t&m, fixed project pricing. Minimum engagement starts at $75K. A discovery call is required to get project-specific quotes.
What tech stack does Ciklum use?
Ciklum works with Python, TensorFlow, PyTorch, AWS, Azure, GCP, Kubernetes, Apache Spark. Primary industries served include Financial Services, Retail & E-commerce, Healthcare & Life Sciences, Media & Entertainment, SaaS & Technology.
Is Ciklum right for enterprise?
FinTech, Retail, Healthcare enterprises — AI product engineering at scale. 3,000+ team size. Key consideration: $75K minimum limits accessibility for smaller ML projects.
What are the best Ciklum alternatives?
The best alternatives to Ciklum depend on your use case. Top options are:
- Tensorway: boutique ml depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ml services market
- LeewayHertz: among the earliest boutique firms to build a structured genai delivery framework — deep llm orchestration and rag pipeline experience
- Scopic: engineers custom ml architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline
Compare Ciklum with other Machine Learning Development companies
Ciklum vs Tensorway Ciklum vs LeewayHertz Ciklum vs Scopic Ciklum vs InData Labs Ciklum vs DATAFOREST Ciklum vs Forte Group Ciklum vs RTS Labs Ciklum vs Quantiphi Ciklum vs N-iX Ciklum vs Miquido Ciklum vs Algoscale Ciklum vs STX Next Ciklum vs Intellias Ciklum vs ScienceSoft Ciklum vs Simform Ciklum vs Oxagile Ciklum vs Softeq Ciklum vs Aimprosoft Ciklum vs Uvik Software Ciklum vs Iflexion Ciklum vs Itransition Ciklum vs DataToBiz Ciklum vs BairesDev Ciklum vs Andersen Lab Ciklum vs Intuz Ciklum vs Tredence Ciklum vs Codiant Ciklum vs GlobalLogic (Hitachi) Ciklum vs EPAM Systems Ciklum vs Cognizant Ciklum vs Accenture Ciklum vs DataRobot