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Service

Custom AI
Development

ML models, LLM pipelines, and AI features built for production — not proof-of-concepts that impress in demos but break under real load. We've been building with AI tools ourselves for years.

What you get

AI that ships to production,
not the demo stage.

LLM integration & RAG pipelines

We build retrieval-augmented generation systems that give your LLM accurate, context-aware responses — not hallucinations. OpenAI, Anthropic, open-source models.

Custom ML models

Classification, regression, anomaly detection, recommendation engines. PyTorch and scikit-learn, trained on your data, validated against your metrics.

AI feature development

Adding AI capabilities to your existing product: smart search, intelligent recommendations, automated classification, document processing, generative features.

Vector databases & embeddings

Semantic search and similarity infrastructure using Pinecone, Weaviate, pgvector. We design embedding pipelines that stay fresh as your data grows.

AI agents & automation

Multi-step AI workflows that take real actions — browsing, coding, summarising, routing. LangChain, LangGraph, and custom orchestration for reliable agentic behavior.

Model fine-tuning

Fine-tune foundation models on your domain-specific data. Get specialist-level performance without building from scratch — and without losing the general capability.

Process

From use case to
production model — structured.

I

Use case audit

We assess your data, your constraints, and what AI can realistically deliver. No hype — honest scoping.

II

Proof of concept

Rapid prototype with real data. We validate that the approach works before committing to production build.

III

Production build

Full implementation with monitoring, evaluation, and CI/CD. Production AI needs observability as much as any backend service.

IV

Iteration & improvement

AI systems improve with data. We set up feedback loops so your model gets better the more you use it.

Ready-to-ship solutions

Common AI use cases,
deployed in weeks.

Pre-scoped solutions for the most in-demand AI problems. Pick what fits your business — or combine several.

AI Voice & Phone Agent

"A receptionist that never sleeps"

Handles inbound calls: books appointments, answers FAQs, checks reservation status, routes urgent calls to humans. Turnkey — no new hardware needed.

Good for: clinics, salons, restaurants, hotels, auto dealers

Handles 60–80% of routine calls without staff involvement

Twilio · Whisper · ElevenLabs · LangGraph · calendar & booking integrations

AI Lead Qualification Agent

"Qualify leads while you sleep"

Engages website visitors in conversation, qualifies them by asking the right questions, scores fit, and books a sales call directly into the calendar. Syncs with CRM automatically.

Good for: B2B services, real estate, consultancies, agencies

Response time drops to under 60 seconds; 25–30% lift in qualification rates

LangChain · OpenAI · HubSpot/Pipedrive · Calendly/Cal.com

Knowledge Base Chatbot

"Answer every question, 24/7 — from your own data"

A conversational chatbot trained on your documents: product catalogs, FAQs, policies, price lists. Customers or staff get accurate answers, not hallucinations.

Good for: e-commerce, clinics, law firms, HR teams, SaaS support

Deflects 50–70% of repetitive support queries

RAG pipeline · Anthropic Claude · OpenAI · Pinecone or pgvector · embeddable widget

Document Intelligence & Data Extraction

"Stop re-typing what's already written"

Extract structured data from invoices, contracts, applications, or receipts. Classify, summarise, and route documents automatically — no more manual entry.

Good for: accounting firms, logistics, legal, insurance, real estate

Cuts document processing time by 80–90%

Claude · OpenAI vision models · LangChain · custom extraction schemas · webhook output

Email & Inbox Automation Agent

"Your inbox, handled"

Monitors a shared inbox, classifies incoming messages, drafts context-aware replies, triggers workflows, and flags only what genuinely needs human attention.

Good for: customer service teams, sales, operations, any busy shared inbox

Saves 5–10 hrs/week per team member on email triage

Gmail/Outlook API · LangGraph · OpenAI · Zapier/Make for downstream actions

Business Workflow Automation Agent

"Your most repetitive task, automated"

A custom AI agent that handles one well-defined back-office workflow end-to-end: weekly reports, data sync between tools, follow-up reminders, CRM updates after calls.

Good for: operations managers, sales ops, any team doing the same thing 20×/week

Replaces 2–4 hrs/day of repetitive manual work

LangGraph · OpenAI · n8n / Make / Zapier · your existing tools via API

AI Product & Content Generator

"10× your content output without 10× the team"

Generates product descriptions, SEO blog posts, social copy, and email newsletters at scale — trained on your brand tone and connected to live product or inventory data.

Good for: e-commerce, marketing agencies, retail, hospitality

Content that used to take days produced in minutes, on-brand

OpenAI · Claude · custom brand style system · CMS/Shopify API integration

Sales Copilot for CRM

"AI that preps your reps before every call"

Enriches CRM records with AI summaries, suggests next best actions, drafts personalised outreach emails, and generates deal status summaries — all inside the existing CRM.

Good for: B2B sales teams of 2–20 people

Reps spend less time on admin and more time closing

HubSpot/Pipedrive API · OpenAI · LangChain · email integration

Personal AI Assistant

"Your own AI, built around the way you work"

A private, personalised AI assistant built on OpenClaw — learns from your documents, emails, and workflows; handles scheduling; drafts responses; and surfaces the right information when you need it.

Good for: executives, consultants, legal professionals, knowledge workers

Hours saved daily on research, drafting, and information retrieval

OpenClaw · RAG pipeline · calendar & email integration · private deployment

AI development team
"We'd tried two other agencies that delivered demos. Edgeware delivered a system that's been in production for 18 months."

AI in production looks very different from AI in a notebook. We've learned what that means the hard way — so you don't have to.

Expertise

The AI stack we work with.

LLM & Foundation Models

OpenAI ChatGPTAnthropic ClaudeLlama 3GeminiMistral

ML Frameworks

PyTorchscikit-learnHugging FaceXGBoostTensorFlow

Orchestration & Retrieval

LangChainLangGraphPineconepgvectorWeaviate

Infrastructure

AWS SageMakerGCP Vertex AIModalWeights & Biases

Common questions

What clients usually ask first.

Do we need a lot of data to start?
It depends on the use case. For LLM-based systems, you can start with relatively little data using prompt engineering and RAG. For custom ML models, we'll assess your data during the discovery phase and be honest about whether it's sufficient.
How do you handle AI accuracy and reliability?
We build evaluation frameworks from day one — not as an afterthought. Every AI system we deploy has defined metrics, test sets, and monitoring in place before it goes live. You'll know what "working correctly" means and be able to measure it.
Can you work with our existing data infrastructure?
Yes. We integrate with your existing data warehouse, databases, or data pipelines. We don't require you to migrate to a new stack — we work with what you have and suggest improvements where they genuinely make sense.
What does the AI cost to run in production?
We model infrastructure costs during discovery and include cost projections in our proposals. We're also deliberate about model selection — using smaller, cheaper models where they perform adequately rather than defaulting to the most expensive option.

Ready to build AI that
actually ships?

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