Custom AI Application

Claude-Powered Apps
That Live Inside Your Stack.

Custom AI business applications. Agents, RAG, MCP servers wired into your CRM and stack. Book a Blueprinting Session.

Two Practices, One Discipline
Custom Applications + AI Agents.

When off-the-shelf doesn't fit and a Zoho deployment isn't the right shape, we build the missing piece. Where Claude-level intelligence would replace a person or a spreadsheet, we build the agent to do it. Often both, in the same engagement.

CUSTOM APPLICATIONS

Web apps, dashboards, and internal tools when the standard product doesn't fit.

Client portals, partner extranets, internal dashboards
Next.js + Supabase or Zoho Creator, chosen for the job
Full source-code handover — owned by you
CLAUDE AI SOLUTIONS

Claude-powered agents wired into your existing tools — no humans in the loop.

Lead scoring + qualification agents
Document generation from your templates
Knowledge-base Q&A bots (RAG + MCP)
Step One — Always
The Scope Engagement

Every project starts here. No exceptions.

Starting Point
Scope / Blueprinting

A fixed-fee discovery engagement. We audit the workflow you want to automate, interview the humans doing it today, map the data + integrations required, and deliver a comprehensive AI build blueprint — before a single line of code is written.

Duration
2–4 weeks
Pricing
Fixed Fee
Best for
Every new client
What you get
Workflow & data audit
Stakeholder interviews
AI build blueprint doc
Model + integration selection
Human-in-the-loop plan
ROI estimates per use case
SAMPLE READINESS ASSESSMENT
AI Feasibility — Q4 Scope
GO
78 SCORE
READY TO BUILD
Data volume + workflow clarity are strong. One integration blocker to solve first.
Data Readiness 88%
Use-Case Clarity 92%
ROI Viability 72%
Integration Complexity 58%
RECOMMENDED STACK
from 3 evaluated
Claude Sonnet 4 Custom RAG MCP
Delivered as blueprint doc + go/no-go recommendation
Deep Dive
Your Business Generates Data All Day.
Most of It Never Gets Used.

We build AI systems that actually work inside your existing tools — not standalone demos. Claude-powered agents connected to your CRM, your docs, your data, doing real work without needing a human in the loop.

01
Lead Scoring Agents

Autonomous agents that analyze engagement signals and rank your pipeline automatically. Reps call the right deals first.

OutcomeRanked pipeline
02
Document Generation

Proposals, contracts, SOWs generated from CRM data in seconds — trained on your templates, brand-voice, and pricing rules.

OutcomeFaster close
03
Internal Q&A Assistants

RAG-powered assistants that answer questions from your knowledge base — like an intern who's read every doc.

OutcomeFewer tickets
04
Automated Reporting

Weekly reports that narrate your data in plain English — no dashboard-crawling required. Delivered to Slack or email.

OutcomeExec visibility
05
Client Portals + Extranets

CRM-tied portals with role-based access and full audit trail — the interface layer that makes your AI stack shippable to customers.

OutcomeClient experience
06
MCP Servers

Model Context Protocol servers exposing your internal tools to Claude directly — agents that can act, not just chat.

OutcomeAction-capable AI
Each of these took
3–12 WEEKS
FROM SCOPE TO GO-LIVE
Claude APIMCP ServersCustom RAGNext.jsSupabaseZoho DelugeWebhooksZoho Creator
What We Build
Four Layers of the AI Build

Every custom AI engagement draws from all four layers — apps, consulting, capabilities, and end-to-end delivery — to solve your actual problem, not to demo a model.

01 — AI-Powered Apps
Your Business Generates Data All Day. Most of It Never Gets Used.

We build AI systems that actually work inside your existing tools — not standalone demos. Claude-powered agents connected to your CRM, your docs, your data, doing real work without needing a human in the loop.

Lead scoring & qualification agents that analyze engagement signals and rank pipeline automatically
Document generation bots — proposals, contracts, SOWs — trained on your templates
Internal Q&A assistants that answer questions from your knowledge base
Automated reporting that narrates your data in plain language every week
Claude APIZoho DelugeWebhooksCustom RAGMCP Servers
malicads-agency.app/dashboard DEPLOYED
MA
MALICAD'S
AGENCY
Dashboard
Leads
Transactions
Contacts
Properties
Documents
Campaigns
DM
Daniel Malicad
Broker
Dashboard
🔔
DM
Good evening, Daniel
Tuesday, June 2, 2026
Active Leads
12
+4 this week
Active Listings
7
7 properties
Pending Closings
4
4 converted
Revenue YTD
$
$460,200
5 agents
Recent Activity View All
DM
Daniel Malicad moved lead to Showing Scheduled Howard Zhao
9w ago
PC
Priya Calderon added new lead Trevor Ferraro
9w ago
EA
Elena Adeyemi uploaded Inspection Report 2310 Riverside Dr
9w ago
PC
Priya Calderon submitted offer for Philip Fujimoto — $510,000
9w ago
CA
Caleb Atienza moved lead to Under Contract Eric Salgado
9w ago
OL
Omar Lucena scheduled showing for Imani Okeke — 1015 Bate Ave
9w ago
Agent Performance Commission YTD
DM
Daniel
Malicad
$142,500
PC
Priya
Calderon
$87,300
OL
Omar
Lucena
$63,200
EA
Elena
Adeyemi
$95,800
CA
Caleb
Atienza
$71,400
02 — Business Consulting
Most Technology Problems Are Actually Process Problems in Disguise.

We map your processes, challenge your assumptions, and build a technology roadmap you'll actually execute. Strategy without implementation is just a document. We do both.

Full technology audits — what you have, what you're paying, what's redundant, what's missing
Automation opportunity mapping with ROI estimates for each identified workflow
Pre-ERP blueprinting to avoid the most common implementation failure modes
Vendor selection — independent advice on the right tools for your actual use case
Process MappingROI AnalysisTech AuditGap Analysis
Scope Deliverable — Sample
AUTOMATION OPPORTUNITY #1
Invoice → CRM → Project Creation
Currently: 45 min manual. Automatable in: 3 days. Est. annual saving: $18,400
AUTOMATION OPPORTUNITY #2
Support Ticket → AI Triage → Assign
Currently: 2-4h SLA breach risk. Automatable in: 5 days. Est. saving: $31,200
AUTOMATION OPPORTUNITY #3
Contract Generation from Deal Close
Currently: 90 min legal review. Automatable in: 2 weeks. Est. saving: $54,000
Total identified: $103,600/yr →
03 — Core AI Capabilities
Beyond Text Generation. Systems That Actually Do the Work.

AI is not one technology — it's four different domains, each with its own tooling. We build the specialist system for the domain that fits your problem, instead of forcing every problem into a chatbot.

Generative AI & multi-agent systems — autonomous agents that track material delays and coordinate with logistics to adjust schedules
Intelligent automation & document processing — custom NLP pipelines for extraction, semantic search, contract analysis
Predictive & prescriptive analytics — demand forecasting, predictive maintenance, dynamic pricing
Computer vision — medical imaging, manufacturing defect detection, retail security video
ClaudeLangChainQdrantPyTorchYOLO
The Four Domains We Build For
Generative AI
Multi-agent systems that plan & act
Doc Processing
NLP for extraction & search
Predictive Analytics
Forecasting, maintenance, pricing
Computer Vision
Imaging, defect detection, video
One brief → the domain that actually fits → the specialist build
04 — End-to-End Service Offerings
A Four-Phase Pipeline. Not a Weekend Hackathon.

Building custom AI is vastly different from building traditional software. Our engagement follows a proven four-phase pipeline that de-risks each stage before the next one starts — strategy first, data second, model third, deployment last.

Phase 1 — Strategy, feasibility & governance: AI readiness assessment, ROI + data-availability study, responsible-AI guardrails (GDPR / HIPAA / EU AI Act)
Phase 2 — Data engineering & pipeline development: preparation, annotation & labeling, vector database architecture (pgvector / Qdrant)
Phase 3 — Model development, tuning & integration: fine-tuning + RAG, explainable AI (XAI), custom interface engineering (dashboards, APIs, voice)
Phase 4 — Deployment & MLOps: edge/cloud deployment, drift & performance tracking, infrastructure cost optimization
RAGFine-TuningXAIMLOpsEdgeCloud
AI Build Pipeline — Live Sample
1 · Strategy & Feasibility
100%
2 · Data Engineering
100%
3 · Model Dev + RAG
72%
4 · MLOps + Drift
18%
MODEL
Claude Sonnet 4
Fine-tuned + RAG
STATUS
On Track
Go-live: Week 11
SOC 2 Ready Zero data retention Explainable
Proof of Concept Lab
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FAQ
Custom AI Application — What Clients Ask.
When should we build custom vs. use an off-the-shelf tool?+
Off-the-shelf first. Every time. If Zoho or an existing SaaS covers 80% of what you need, deploy that. Custom is for the cases where your workflow is your competitive edge and no product does it — or where AI can automate work that's currently done manually. Scope tells us which it is.
Who owns the code we pay you to build?+
You do. Full source-code handover at the end of every engagement — hosted on your GitHub, deployed to your cloud accounts, secrets in your vault. We keep no proprietary lock-in. If you switch vendors five years from now, everything works exactly the same.
Which AI models do you use?+
Primarily Claude (Anthropic) — Sonnet or Opus depending on the task. GPT and Gemini when the customer has a strong preference or when a model is specifically better for their use case. Model choice is part of the Scope engagement; we run head-to-head evals for each build.
How do you handle data privacy? Does our data train the AI?+
No. We use API-tier access with the Anthropic Zero-Data-Retention agreement (or equivalent for other providers). Your data is never used for model training. We can also run open-weight models on your own infrastructure when the compliance bar demands it.
Can the AI agent integrate with our existing Zoho stack?+
Yes — that's often the whole point. Agents read from and write to CRM records, trigger workflows via Deluge or Flow, populate Creator forms, and post to SalesIQ. If it has an API, the agent can call it.
How long does an AI project take?+
A tightly-scoped agent (single workflow, single integration) is 3–6 weeks. A full custom application with multiple AI features and integrations is 3–6 months. Scope defines the exact number and what “done” looks like.
What if the AI gets something wrong?+
Every agent is designed with the right level of human oversight for the task. High-stakes actions (send email, close deal, refund payment) require confirmation. Low-stakes classifications (route lead, tag document) run autonomously with a review dashboard. We calibrate the loop during Scope.
Do you handle hosting and ongoing maintenance?+
Yes. Vercel, Supabase, AWS, or your existing cloud — we deploy to whichever platform you're already on. Ongoing maintenance either through Infinity Mirror (fixed-fee ongoing partnership) or Bank of Hours (as-needed) after go-live.
Ready to Build the AI Piece?

Every AI project starts with a fixed-fee Scope engagement — we identify the workflow to automate, define what “done” looks like, and run a model eval before any code is written.

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Mirror Advisors
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