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Mavlers.ai

AI Development

Building intelligence. From retrieval systems grounded in your own trusted knowledge to autonomous agents that complete real work, we architect and ship production-grade AI your users actually adopt.

RAG AgentsCustom AI AppsAI AgentsLLM IntegrationAI Dashboards
RAGKnowledge Intelligence

RAG Agent Development

Agents that answer from your own trusted, access-controlled knowledge — with citations, not hallucinations.

Typical stack
pgvectorPineconeLangChainOpenAI / Claude
Business outcome

Staff and customers get fast, trustworthy answers from your content — cutting search time and support load.

What we build
  1. 01Retrieval-augmented assistants over documents, wikis, tickets and databases
  2. 02Citation-backed answers that link to the exact source passage
  3. 03Access-controlled retrieval that respects user roles and permissions
  4. 04Ingestion pipelines that keep the knowledge base continuously fresh
Engineering detail
  1. 01Chunking, embeddings and hybrid (semantic + keyword) retrieval
  2. 02Re-ranking and query rewriting to lift answer precision
  3. 03Vector store setup (pgvector, Pinecone, Weaviate) with metadata filters
  4. 04Evaluation harness for groundedness, relevance and hallucination rate
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AIAI Engineering

Custom AI Application Development

Bespoke AI applications, copilots and intelligent interfaces built around a specific need.

Typical stack
Next.jsReactNode / PythonLLM APIs
Business outcome

A production-grade AI product your users actually adopt — not a fragile prototype.

What we build
  1. 01Full-stack AI web apps, portals and internal tools
  2. 02Copilots and assistants embedded into existing products
  3. 03Streaming chat interfaces with tools, memory and history
  4. 04Admin, analytics and feedback dashboards
Engineering detail
  1. 01Modern front end (React / Next.js) with streaming responses
  2. 02Prompt orchestration, function calling and structured output
  3. 03Auth, multi-tenancy and usage metering built in
  4. 04Cost, latency and quality monitoring per feature
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AGAI Engineering

AI Agent Development

Tool-enabled agents — single or multi-agent — that complete real business tasks end to end.

Typical stack
LangGraphFunction callingMCPVector memory
Business outcome

Repetitive, multi-step work gets handled autonomously — with humans in control of what matters.

What we build
  1. 01Goal-driven agents that plan, call tools and act
  2. 02Multi-agent systems with specialised roles and coordination
  3. 03Human approval and guardrails for sensitive actions
  4. 04Persistent memory and context across sessions
Engineering detail
  1. 01Tool/function schemas with strict input validation
  2. 02Planning loops with step limits, timeouts and fallbacks
  3. 03Observability: full trace of reasoning, tool calls and outcomes
  4. 04Evaluation and regression testing on task success rate
Powered by our Model Context Protocol work →
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LLMAI Engineering

LLM Integration

Integrate and route between leading models with cost, latency and quality controls built in.

Typical stack
OpenAIAnthropicOpen modelsGateways
Business outcome

The right model for each job — with predictable cost, quality and no single-vendor lock-in.

What we build
  1. 01Model integration into apps, workflows and backends
  2. 02Provider-agnostic routing across OpenAI, Anthropic and open models
  3. 03Prompt management, versioning and A/B testing
  4. 04Guardrails, moderation and PII handling
Engineering detail
  1. 01Model routing by task, cost and latency budgets
  2. 02Caching and batching to control token spend
  3. 03Structured output with schema validation and retries
  4. 04Fallback chains for provider outages or rate limits
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BIBusiness Intelligence

AI-Driven Automated Dashboard Development

Building a custom business dashboard is a challenge for every team — we build AI-driven dashboards that assemble themselves and turn scattered data into clear business insights.

Typical stack
Next.jsPostgres / BigQueryLLM APIsCharting
Business outcome

Every team sees the metrics that matter — with AI explaining the story behind them — instead of waiting on hand-built reports.

What we build
  1. 01Custom, branded dashboards that unify data from every tool you run
  2. 02AI-generated narratives that explain what changed, and why
  3. 03Natural-language querying — ask a question, get the chart and the answer
  4. 04Automated alerts, anomaly detection and recommended next actions
Engineering detail
  1. 01Automated data pipelines that model and refresh your metrics on schedule
  2. 02An LLM layer that summarises trends and surfaces insights, not just numbers
  3. 03Role-based views and access control for internal teams and clients
  4. 04Embeddable, responsive dashboards with exports and scheduled reports
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Across every engagement

The engineering foundations we bring to all of it

Security by design

Role-based access, scoped credentials, data isolation and audit logging.

Human-in-the-loop

Approval gates and guardrails wherever judgement or risk demands them.

Observability

Tracing, logging and evaluation so you can see and trust what runs.

Technology agnostic

We pick the right models and tools for the job, not a fixed stack.

Production-grade

Testing, CI/CD and monitoring — engineered to run, not just to demo.

Data governance

PII handling, retention controls and responsible-AI practices.

Flexible engagement

Work with us directly, or as a behind-the-scenes delivery partner.

Ongoing support

Maintenance, optimization and model updates after launch.

Browse real AI use case patterns across industries and the digital lifecycle

The workflows, agents and integrations we build — from marketing and sales to support, operations and internal productivity.

View Our AI Use Cases →

Have a service requirement in mind?

Tell us the problem or the capability you want to build. We'll map it to the right approach and team.

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