Zaply
Zaply
Services · AI & Data

Integrate AI into the systems your business already runs.

We implement language models, agentic workflows, and retrieval pipelines directly into your existing CRMs, ERPs, databases, and internal tools — selecting the right architecture and model for your specific use case.

Talk to the teamMVP in 4 weeks · Production in 8–12
Language ModelsAgentic WorkflowsRAG PipelinesCRM IntegrationERP IntegrationAPI ConnectorsDocument ProcessingAutomation

01What we deliver

What it takes to go from use case to production

  • Production-ready AI system

    A tested system running in your environment with real data, users and load from launch.

  • Model selection & fine-tuning

    We compare general and specialised models against your use case and tune the best performer with prompting or fine-tuning. The architecture lets you switch providers.

  • System integration

    REST APIs, webhooks and connectors to your CRM, ERP, databases and internal tools, so AI works inside the workflows your team already uses.

  • Monitoring & continuous improvement

    Dashboards tracking accuracy, latency, token cost, and failure rates. Drift detection, alert thresholds, and a feedback loop that improves the model from real usage data.

02Why us

Why work with Zaply

We build systems designed to run in production, integrated with your stack and monitored from day one.

  • Production-first mindset

    We design every system for production from the start: real data, real users and edge-case handling.

  • Model-agnostic selection

    We compare the leading models against your use case and recommend the best fit, without depending on a single provider.

  • Full-stack AI expertise

    We cover everything from data pipelines and model integration to deployment and monitoring.

  • Built-in observability

    Every system ships with logs, traces, dashboards and alerts so you can see what happens, what fails and what improves.

03Tech stack

Technologies we use

We choose each component based on the use case, budget and who will maintain the system.

AI models
Large language models · Multimodal models · Domain-specific models · Open-source models
LLM orchestration
Agent frameworks · Chain orchestration · Multi-agent systems
Vector databases
Semantic search · Embedding stores · Hybrid retrieval systems
Cloud & infrastructure
Managed AI APIs · Self-hosted inference · Edge deployment
Integration layer
REST APIs · Webhooks · CRM/ERP connectors · Internal tools
Observability
Trace logging · Quality dashboards · Cost tracking · Drift detection

04How it works

From definition to production in 8 to 12 weeks

  1. 01

    Define

    We agree on scope, success metrics, data sources and integration points before development starts.

  2. 02

    MVP in 4 weeks

    A working system connected to real data that covers the main scenarios. Internal users start testing it and we document edge cases.

  3. 03

    Integrate & harden

    We connect the AI to your stack, run load tests, add error handling and define when to escalate to a person.

  4. 04

    Deploy & hand over

    Launch with runbooks, monitoring in place and a handover session so your team can run and improve the system.

05Areas of application

Where does this apply in your organization?

Examples of applications by business area.

Customer Service

  • Automatic ticket classification
  • AI chatbot deployment

Sales & Marketing

  • Email marketing automation
  • Predictive lead scoring system

Finance & Accounting

  • Automatic bank reconciliation
  • Intelligent invoice processing

Human Resources

  • Automated onboarding workflows
  • Payroll & absence automation

Operations & Logistics

  • Delivery route optimization
  • AI-powered visual quality control

IT & DevOps

  • Incident response automation
  • Automated deployment pipelines

Have a use case ready to build?

We review your use case, propose an architecture and give you a time and cost estimate.

Request an assessment