Understanding the overarching trends of your business and overall market saves you time, money and energy in the long run, and can help you dominate your market.

What we deliver?

Faster time-to-value

from PoC to production without “demo debt”

Trust & compliance

governance, security, and audit-friendly delivery

Stable performance

evaluation, monitoring, and continuous improvement loops

Cost control

right-sized architectures, FinOps-aware inference and training

Our AI/ML service areas

1) Generative AI (LLM) Solutions

Ship practical GenAI—internal copilots, customer assistants, knowledge search, process copilots, and agentic automations.

Typical deliverables

• RAG systems (vector search + retrieval + grounding)

• Enterprise copilots (HR/IT/Support/Operations)

• Multi-agent workflows (task routing, tool calling, approvals)

• LLM evaluation (quality, safety, hallucination tests)

• Guardrails & policy enforcement (PII, toxicity, jailbreak resilience)

Best-fit tech: Azure OpenAI / OpenAI / AWS Bedrock / Vertex AI, vector DBs, embeddings, prompt orchestration, tool integrations.

2) Machine Learning & Advanced Analytics

Turn structured + unstructured data into measurable business impact.

Capabilities

• Predictive analytics (risk, churn, fraud signals, propensity)

• Forecasting (demand, staffing, inventory, capacity)

• Recommendations & personalization

• Anomaly detection (ops, finance, security, IoT)

• NLP & document intelligence (classification, extraction, summarization)

3) Intelligent Automation (AI + Workflows)

Automate real processes end-to-end—not just models.

What we automate

• Approval & finance workflows (invoice/expense/vendor)

• ITSM routing + auto-remediation (tickets → actions)

• CRM ↔ ERP reconciliation (sync, matching, exceptions)

• Compliance workflows (KYC/KYB steps, evidence collection)

• Document-centric processes (IDP + validation + routing)

Workflow platforms: n8n, event-driven architectures, APIs, queues, audit logs.

4) MLOps / LLMOps & AI Platforms

Make AI operational: reproducible, governed, monitored, and scalable.

Platform building blocks

• Model lifecycle: experiment tracking, registry, CI/CD

• Data lifecycle: quality checks, lineage, feature stores

• Deployment: batch, real-time, streaming, edge

• Observability: drift, latency, cost, SLO/SLA dashboards

• Governance: access, approvals, policy-as-code, auditability

Adoption paths for Generative AI

Adopt (Pay & Use)

use a third-party GenAI tool with minimal customization

integrate an LLM into your product/workflows

RAG + your knowledge + permissions

Embed (Integrate Your Apps)

Ground (Enrich with Your Data)

A pragmatic progression—start where you are, expand as value proves out.

Own (Train/Fine-tune on Your Data)

custom model behavior, stronger control/IP

“Your AI Journey”

AI Readiness & Value Workshop (2 days) → use-case shortlist, architecture options, risk & compliance map, roadmap with quick wins.

Then we move into:

• Discovery Sprint (1–2 weeks): data + process mapping, success metrics

• MVP (4–8 weeks): working solution in your environment

• Scale (8–16+ weeks): hardening, governance, rollout, training

• Operate: managed improvements, monitoring, and optimization

Our Services

Tailored solutions for enterprise knowledge and customer support.

1. Enterprise Knowledge Copilot (RAG)

• Short: Secure internal search + Q&A across docs, wikis, tickets.

• Common in: Enterprises, Telecom, Fintech, Shared services

• Typical buyers: CIO, Head of Support, Ops leaders

2. GenAI Customer Assistant (CX)

• Short: Omnichannel assistant with escalation, audit logs, and guardrails.

• Common in: Retail, Airlines/Travel, Telecom, Banking

• Typical buyers: CX Director, Contact Center, Product

3. Document Intelligence (IDP)

• Short: Extract, validate, and route data from PDFs/scans/contracts.

• Common in: Banking, Insurance, Healthcare, Public sector

• Typical buyers: COO, Compliance, Operations

4. Fraud / Risk Signal Modeling

• Short: ML risk scoring with explainability and monitoring.

• Common in: Banking, Fintech, Payments, Marketplaces

• Typical buyers: Risk, Fraud, Compliance

5. Demand & Inventory Forecasting

• Short: Forecasting pipelines with scenario planning and dashboards.

• Common in: Retail, eCommerce, Manufacturing, CPG

• Typical buyers: Supply Chain, Planning, Finance

6. Anomaly Detection (Ops & Finance)

• Short: Detect unusual patterns in metrics, transactions, or logs.

• Common in: High-traffic platforms, Telecom, Fintech, SaaS

• Typical buyers: SRE, Finance Ops, Security

7. Predictive Maintenance / Quality Signals

• Short: ML for equipment health, defect detection, process optimization.

• Common in: Manufacturing, Logistics, Energy

• Typical buyers: Plant Ops, Engineering, Quality

8. ITSM Automation & Routing

• Short: Tickets → triage → routing → runbooks → closure.

• Common in: Enterprises, Telecom, Managed services

• Typical buyers: IT Ops, SRE, Service owners

9. CI/CD Quality Gates with AI

• Short: Intelligent checks for security, quality, and release readiness.

• Common in: Regulated industries, Enterprise IT, Fintech

• Typical buyers: DevOps, AppSec, Platform teams

10. MLOps / LLMOps Platform Foundation

• Short: Reproducible pipelines, registry, deployment, monitoring.

• Common in: Enterprises, SaaS, Regulated orgs

• Typical buyers: Head of Data/AI, CTO, Platform

11. Workflow Automation (n8n) + AI

• Short: Human approvals + AI steps + integrations across tools.

• Common in: SMEs to enterprises, ops-heavy teams

• Typical buyers: Operations, Finance, IT

12. AI Safety: Evaluation, Guardrails, Monitoring

• Short: Policy controls, red teaming, eval harness, production monitoring.

• Common in: Regulated, Large enterprises, GenAI at scale

• Typical buyers: Security, Compliance, AI governance

Industries we commonly support

We work across Banking & Fintech, Telecom, Retail & eCommerce, Manufacturing & Logistics, Healthcare, and Enterprise IT—with delivery coverage across Turkey (Istanbul), Germany (Cologne), and the broader EMEA region.

Security, privacy & responsible AI (built-in)

• Data access controls (RBAC/ABAC), tenant boundaries

• PII handling, retention policies, audit trails

• Model evaluation for hallucinations and unsafe outputs

• Secure deployment patterns (private networking, key management)

• Compliance-ready documentation and change management

FAQs

How fast launch?

Most teams validate a focused pilot in 4 to 8 weeks.

Cloud support?

We design vendor-neutral solutions for Azure, AWS, and Google Cloud.

On-prem system integration?

Yes, our workflows and retrieval-augmented generation adapt to your on-premises security and infrastructure.

How reduce hallucinations?

We combine grounding with careful data curation to minimize errors.

What about hybrid clouds?

Hybrid approaches are fully supported to fit your environment.

Can you handle complex data access?

Yes, we tailor integrations to your data access needs and security policies, ensuring smooth operation.

Contact us

Whether you have a request, a query, or want to work with us, use the form below to get in touch with our team.