How We Use AI | AI Agents, Automation & Intelligent Solutions — Lenka Studio
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How We Use AI

We don't just sell AI — we use it every day to deliver better work, faster. And we build it for clients who want results, not hype.

AI is a tool, not a replacement. Every AI output at Lenka Studio is reviewed, refined, and approved by a human expert. We use AI to amplify what our team does best — think strategically, design with intent, and build with precision.

Our AI Principles

How we think about AI

Human Oversight Always

Every AI output is reviewed, refined, and approved by our team. AI suggests; humans decide. No exceptions.

Full Transparency

You always know when and how AI is being used in your project. No hidden automation, no black boxes.

Data Privacy First

Your data is never used to train third-party models. We follow strict data protection practices across every tool we use.

Quality Over Speed

AI helps us move faster, but never at the cost of craft. The time saved goes back into strategy, refinement, and thinking.

AI in Our Daily Work

We practice what we build

01
Design

Research & Design Exploration

AI accelerates our design research, generates layout variations, and helps us explore more creative directions in less time — so our designers focus on the decisions that matter.

What AI Does
  • Competitive research synthesis
  • Rapid layout prototyping
  • Copy drafts for mockups
  • Image generation for concepts
What Humans Do
  • Final design decisions
  • Brand alignment & art direction
  • User experience strategy
  • Client presentation & iteration
02
Development

Smarter Code, Faster Shipping

AI-powered code assistance helps us write cleaner code, catch bugs earlier, and automate repetitive development tasks — while our engineers own every architecture decision.

What AI Does
  • Code review assistance
  • Test generation & coverage
  • Documentation drafting
  • Bug pattern detection
What Humans Do
  • Architecture & system design
  • Security review & best practices
  • Performance optimization
  • Code ownership & deployment
03
Content

Content That Sounds Human

AI generates first drafts and variations that our content team shapes into compelling, on-brand copy. Every word is human-edited to match your voice and audience.

What AI Does
  • First draft generation
  • SEO keyword research
  • Content variation testing
  • Translation assistance
What Humans Do
  • Brand voice & tone refinement
  • Strategic messaging
  • Editorial judgment
  • Final approval & publishing
04
Operations

Automated Workflows & Operations

From project management to internal knowledge retrieval, AI handles the repetitive operational tasks so our team can focus on high-impact client work.

What AI Does
  • Automated status updates
  • Internal knowledge Q&A
  • Workflow routing & triggers
  • Reporting & data synthesis
What Humans Do
  • Strategic planning
  • Client relationships
  • Decision-making & prioritization
  • Process improvement
Built for Ourselves First

Our Internal AI Knowledge Assistant

We built an internal ChatGPT-style system where our team can instantly query company SOPs, policies, project guidelines, and operational rules — all through natural conversation. Instead of searching through documents, our employees just ask.

80%
Faster answers
24/7
Always available
100+
Documents indexed
  • Natural language search across all company documents
  • Instant answers about SOPs, rules, and policies
  • Context-aware responses with source references
  • Secure — data stays within our infrastructure
  • Continuously updated as policies change
Lenka Knowledge Base Online
What's our policy on client data handling?
Based on our Data Privacy SOP (v3.2), all client data must be stored in encrypted environments. Third-party AI tools must have DPA agreements in place before use. No client data is used for model training. Full policy details are in section 4.1 of the handbook.
What tools are approved for AI tasks?
Approved tools per our AI Tooling Policy: OpenAI API (enterprise), Claude API (with DPA), n8n (self-hosted), and Vercel AI SDK. All require project-level approval from the tech lead before use.
Ask anything about company policies...
Live Internal Tool
What We Build for You

AI solutions we deliver to clients

(01)

AI Agents & Chatbots

Custom conversational agents for customer support, lead qualification, and internal operations — trained on your data and integrated into your existing systems.

Customer Support Lead Qualification Knowledge Base
(02)

Workflow Automation

Connect your systems, eliminate manual data entry, and trigger intelligent actions based on events. We build automation flows that actually save meaningful hours every week.

Process Automation System Integration Event-Driven
(03)

Content & Marketing AI

AI-powered content pipelines, personalized marketing automation, and dynamic creative optimization that scale your marketing without scaling your team.

Content Generation Personalization Campaign Automation
(04)

Custom AI Integration

Embed AI capabilities directly into your existing products and platforms — from intelligent search and recommendations to document processing and predictive analytics.

API Integration Smart Search Predictive Analytics
How We Work

From idea to production in clear steps

01
Discovery

Understand Where AI Creates Real Value

We start by understanding your business, not your tech stack. We identify where AI creates genuine value — and honestly tell you where it doesn't. Not every problem needs AI, and we'll say so.

02
Assessment

Evaluate Data & System Readiness

We assess your existing data, systems, and workflows to determine what's realistic. This includes data quality checks, integration mapping, and setting clear expectations for outcomes.

03
Build & Test

Develop With Iterative Checkpoints

We build in short cycles with your involvement at every step. Rigorous testing, edge case handling, and human review of AI outputs ensure the solution works in the real world — not just in demos.

04
Deploy & Monitor

Launch With Guardrails, Improve Continuously

We deploy with monitoring, fallback mechanisms, and performance tracking from day one. Post-launch, we continuously improve based on real-world data — because AI solutions get better over time.

Our AI Stack

Tools chosen for the job, not the hype

AI Models & Platforms

OpenAI / GPT

Our primary LLM for conversational AI, content generation, and complex reasoning tasks. Chosen for reliability and broad capability.

Anthropic / Claude

Used for nuanced analysis, long-context tasks, and when safety and accuracy are paramount. Excellent for document processing.

Google Gemini

Multimodal capabilities for projects that combine text, image, and video understanding in a single pipeline.

Automation & Orchestration

n8n

Our core automation platform. Self-hosted for data privacy, extensible with custom nodes, and powerful enough for complex multi-step workflows.

LangChain / LangGraph

Framework for building AI agent systems with tool use, memory, and multi-step reasoning. Essential for complex agentic workflows.

Vercel AI SDK

Streamlined AI integration for web applications. Fast streaming responses and clean abstractions for building AI-powered interfaces.

Data & Infrastructure

Vector Databases

Pinecone, Qdrant, or pgvector — chosen per project. Enables semantic search, RAG (retrieval-augmented generation), and knowledge base systems.

Cloudflare AI

Edge AI inference for low-latency applications. Combined with Workers for serverless AI that runs close to your users worldwide.

Monitoring & Observability

LangSmith, Helicone, and custom dashboards for tracking AI performance, costs, latency, and output quality in production.

Common Questions

Straight answers about AI

We build internal AI tools, customer-facing chatbots, RAG systems for company knowledge bases, agentic workflows that handle multi-step tasks, content generation pipelines, and AI-powered analytics. Most engagements start with one specific use case and expand as ROI is proven.

We use whatever fits the use case. OpenAI's GPT models are strong for general-purpose work. Anthropic's Claude excels at long context and reasoning. Open-source models like Llama and Mistral are often the right call for cost-sensitive or privacy-sensitive deployments. We help clients pick the right one.

For sensitive data we recommend self-hosted or VPC-deployed models, or providers with strong data privacy guarantees. We never let user data flow to public model training pipelines. For client-side automations we can build entirely on-premises or in private cloud environments.

Yes. Most of our AI work is integration, not greenfield. We connect AI capabilities to existing CRMs, databases, ticketing systems, internal tools, and customer-facing apps. Common integration points include Slack, Notion, Salesforce, HubSpot, and custom internal databases.

We define success metrics before building. For internal tools we measure hours saved per week, error rates, or processing time. For customer-facing AI we measure deflection rate, conversion lift, or response quality. We build dashboards that track these metrics live so the value is visible.

There are two cost components: build cost and ongoing token cost. Build costs typically run USD 8,000 to USD 40,000 depending on complexity. Ongoing token costs depend entirely on usage volume — we model expected costs upfront and build in budget controls to prevent runaway spend.

For most use cases we recommend prompt engineering and RAG over fine-tuning, since they're cheaper and easier to update. For specialised domains where prompt engineering hits limits we do fine-tune open-source models. We're transparent about which approach makes sense for your situation.
Ready to Explore AI?

Let's talk about what AI can actually do for your business.

Book a free consultation — we'll assess where AI fits in your operations and give you an honest recommendation. No sales pitch, just clarity.

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