# NextEraLabs — Agentic workforce for data, ML & AI platforms

> NextEraLabs puts a full team of production-ready AI agents to work on your data, ML and AI platforms — building, running, developing and continuously improving them end to end, on AWS, Microsoft Azure and Google Cloud. Designed by engineers with 15+ years of end-to-end data projects.

Canonical page: https://nexteralabs.com/
- 18 agent roles
- 4 layers: platform, data, ML, AI
- 3 hyperscale clouds
- 15+ years of data projects

## What NextEraLabs offers

NextEraLabs provides an agentic workforce: 18 AI agent roles, each with a defined job, the tools for it and a deliverable a human team reviews. The roles are organised two ways: by platform layer (Platform, Data, ML, AI) and by lifecycle crew (Build, Develop, Run, Improve).

### Layer: Platform

The cloud foundation everything else runs on.

#### Architect Agent (ARC)

- Persona: The solution architect
- Lifecycle crew: Build
- What it does: Turns your requirements into a target architecture on AWS, Azure or Google Cloud.
- Works with: Infrastructure Agent, Security Agent, Migration Agent, IT
- Hands back: Reference architecture, decision records

#### Infrastructure Agent (INF)

- Persona: The platform engineer
- Lifecycle crew: Build
- What it does: Provisions environments, networking and identity as code.
- Works with: Architect Agent, Security Agent, Reliability Agent, FinOps Agent, IT
- Hands back: Infrastructure-as-code pull requests, runbooks

#### Security Agent (SEC)

- Persona: The security engineer
- Lifecycle crew: Build
- What it does: Sets up access, secrets and network policy, then checks every change against them.
- Works with: Architect Agent, Infrastructure Agent, Governance Agent, Risk & Compliance
- Hands back: Access model, policy findings

#### Reliability Agent (SRE)

- Persona: The on-call engineer
- Lifecycle crew: Run
- What it does: Watches pipelines and platform, triages incidents, keeps the runbooks current.
- Works with: Infrastructure Agent, Pipeline Agent, MLOps Agent, Quality Agent, IT
- Hands back: Incident notes with root cause, fixes as pull requests

#### FinOps Agent (FIN)

- Persona: The FinOps analyst
- Lifecycle crew: Improve
- What it does: Tracks cloud cost, finds the expensive workloads, proposes the fix.
- Works with: Infrastructure Agent, Performance Agent, Finance
- Hands back: Cost report, right-sizing pull requests

### Layer: Data

Pipelines, models, quality and governance.

#### Migration Agent (MIG)

- Persona: The migration lead
- Lifecycle crew: Build
- What it does: Reads your legacy warehouse — SQL, stored procedures, ETL jobs — and rebuilds it on the target platform.
- Works with: Architect Agent, Pipeline Agent, Quality Agent
- Hands back: Converted models, row-level reconciliation report

#### Pipeline Agent (PIP)

- Persona: The data engineer
- Lifecycle crew: Develop
- What it does: Builds and maintains ingestion and transformation pipelines as reviewed pull requests.
- Works with: Reliability Agent, Migration Agent, Quality Agent, Analytics Agent, Feature Agent, Performance Agent, Refactor Agent
- Hands back: dbt models, orchestration DAGs, pull requests

#### Analytics Agent (ANA)

- Persona: The analytics engineer
- Lifecycle crew: Develop
- What it does: Models the semantic layer, answers business questions and drafts dashboards.
- Works with: Pipeline Agent, Governance Agent, AI Agent, Finance, Sales & Marketing, Operations
- Hands back: Answers with the query shown, dashboards

#### Quality Agent (QA)

- Persona: The data quality engineer
- Lifecycle crew: Run
- What it does: Writes the tests nobody has time for and watches freshness and anomalies.
- Works with: Reliability Agent, Migration Agent, Pipeline Agent, Governance Agent
- Hands back: Test suites, data quality findings

#### Governance Agent (GOV)

- Persona: The data steward
- Lifecycle crew: Run
- What it does: Catalogs, classifies sensitive data, documents lineage, checks policy on every change.
- Works with: Security Agent, Analytics Agent, Quality Agent, Knowledge Agent, Risk & Compliance
- Hands back: Catalog entries, lineage, policy findings

#### Performance Agent (PRF)

- Persona: The performance engineer
- Lifecycle crew: Improve
- What it does: Finds slow queries and jobs and tunes them.
- Works with: Pipeline Agent, FinOps Agent, Refactor Agent
- Hands back: Tuning pull requests with the query plans

#### Refactor Agent (RFX)

- Persona: The maintainer
- Lifecycle crew: Improve
- What it does: Pays down technical debt: unused models, duplicated logic, overdue upgrades.
- Works with: Pipeline Agent, Performance Agent
- Hands back: Cleanup pull requests, deprecation plan

### Layer: ML

Features, training and models in production.

#### Feature Agent (FEA)

- Persona: The feature engineer
- Lifecycle crew: Develop
- What it does: Builds and maintains the feature store that models train and serve from.
- Works with: Pipeline Agent, ML Agent
- Hands back: Feature pipelines, feature documentation

#### ML Agent (MLE)

- Persona: The ML engineer
- Lifecycle crew: Develop
- What it does: Builds training pipelines and runs experiments.
- Works with: Feature Agent, MLOps Agent, Evaluation Agent, Operations
- Hands back: Model candidates with an evaluation report

#### MLOps Agent (MLO)

- Persona: The MLOps engineer
- Lifecycle crew: Run
- What it does: Deploys models, watches drift and triggers retraining.
- Works with: Reliability Agent, ML Agent, Evaluation Agent
- Hands back: Release records, drift reports

### Layer: AI

Assistants and agents on your governed data.

#### Knowledge Agent (KNW)

- Persona: The knowledge engineer
- Lifecycle crew: Develop
- What it does: Prepares documents, embeddings and retrieval indexes for AI applications.
- Works with: Governance Agent, AI Agent, Product
- Hands back: Retrieval indexes, source coverage report

#### AI Agent (AIE)

- Persona: The AI engineer
- Lifecycle crew: Develop
- What it does: Builds assistants and agent workflows on your governed data.
- Works with: Analytics Agent, Knowledge Agent, Evaluation Agent, Sales & Marketing, Product
- Hands back: AI services with their evaluation suites

#### Evaluation Agent (EVL)

- Persona: The evaluator
- Lifecycle crew: Improve
- What it does: Tests models and AI applications against evaluation sets and flags regressions.
- Works with: ML Agent, MLOps Agent, AI Agent, Risk & Compliance
- Hands back: Evaluation reports, regression findings

## Lifecycle crews

- **Build** — Stand the platform up. Roles: Architect Agent, Infrastructure Agent, Security Agent, Migration Agent.
- **Develop** — Ship data, ML and AI products. Roles: Pipeline Agent, Analytics Agent, Feature Agent, ML Agent, Knowledge Agent, AI Agent.
- **Run** — Keep it healthy every day. Roles: Reliability Agent, Quality Agent, Governance Agent, MLOps Agent.
- **Improve** — Make it better every week. Roles: FinOps Agent, Performance Agent, Refactor Agent, Evaluation Agent.

## Business lines

- **Finance** — FinOps Agent, Analytics Agent
- **Sales & Marketing** — Analytics Agent, AI Agent
- **Operations** — ML Agent, Analytics Agent
- **Risk & Compliance** — Governance Agent, Security Agent, Evaluation Agent
- **Product** — AI Agent, Knowledge Agent
- **IT** — Architect Agent, Infrastructure Agent, Reliability Agent

## How it works

1. **Assess** — We map your platform, your backlog and where agents can safely take work.
2. **Deploy** — Agents get a role, tools and guardrails inside your own cloud tenant.
3. **Supervise** — Your team approves. Every action is logged and reversible.
4. **Scale** — Add roles as trust grows. Our engineers stay accountable for the outcome.

## Guardrails

- **Runs in your environment** — Your tenant, your data, your access model.
- **Human approval on every change** — Agents propose through pull requests and tickets. People merge.
- **Everything is auditable** — Each action, query and decision is logged.
- **Platform-native** — Works with the tools you already run. No new lock-in.

## Supported platforms

The workforce works natively on all three hyperscale clouds — single-cloud, multi-cloud or hybrid — and on the open-source stack.

- **AWS**: S3, Glue, Redshift, Athena, EMR, Kinesis, Lake Formation, SageMaker, Bedrock, QuickSight
- **Microsoft Azure**: Fabric, OneLake, Synapse, Data Factory, Stream Analytics, Data Activator, Power BI, Azure Machine Learning, Azure AI Foundry
- **Google Cloud**: BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex, Data Fusion, Composer, Looker, Vertex AI
- **Open source** (on any cloud or on-prem): dbt, Trino, Apache Iceberg, Apache Spark, Apache Flink, Apache Superset, Prefect, Apache NiFi, Keycloak, MLflow
- Data solutions at any scale, anywhere, any tool — SaaS · PaaS · IaaS · On-prem

## Company

NextEraLabs Information Technologies was established in 2020 in İstanbul. We are an expert team that has been implementing end-to-end data projects across many sectors for more than 15 years.

- Industries: e-Commerce, Finance, Telco, FMCG, Manufacturing
- Consultancy services: Cloud data transformation & migration; Data architecture & engineering; DWH modeling, re-engineering, re-factoring; Data lakehouse; Data governance & data quality; Business intelligence; Near-realtime warehousing; DataOps & MLOps; Customer analytics & forecasting; Fraud detection & computer vision

## Contact

- Email: info@nexteralabs.com
- Address: Fenerbahçe Mah. İğrip Sk. No: 13/1, Kadıköy, 34726 İstanbul, Türkiye
- Map: https://www.google.com/maps/search/?api=1&query=40.971571,29.0426549