Multi-Agent Orchestration
Specialist agents plan, execute, review in parallel, and consolidate complex work with bounded feedback loops.
Available for select remote AI builds
AI · agents · automation
AI systems clients can understand—and teams can own.
I’m Cheska Leana Oriño, an AI automation and AI agent engineer. I turn repetitive operations into reliable workflows, useful agents, and client-owned systems with clear boundaries.
workflow / client-ownedsystem online
01
Receive the workForms, email, CRM, messaging, schedules, or APIs.
02
Reason within boundariesRules, memory, tools, approvals, and controlled access.
03
Return a verified resultUpdates, replies, reports, bookings, or human review.
Designed around the business outcomeReady for review
1,300+Public commits behind the flagship agent platform
36Versioned project releases and documented iterations
12+Supported communication and work channels
RemoteDelivery from the Philippines to teams worldwide
What I build
Choose the outcome, not the buzzword.
Each service starts with the workflow your team needs to improve, then uses the smallest reliable mix of automation, AI, and infrastructure.
01
AI Automation
Connect CRM, email, calendars, reporting, and business tools into one dependable workflow.
02AI Agent Development
Build tool-using agents with memory, approvals, clear boundaries, and reliable failure handling.
03Self-Hosted AI Systems
Run client-owned agent infrastructure with isolated execution, controlled credentials, and monitoring.
04OpenClaw Development
Deploy, customize, harden, and connect OpenClaw or Hermes-Agent to real business workflows.
05Remote AI Engineering
Move from workflow discovery to a tested build, documented deployment, and practical handoff.
Use cases
Representative systems for everyday business work.
Each graph maps the starting input through the system to a useful business outcome. Choose the flow closest to the work your team handles today.
Intelligent Data Scraping
Collect, clean, validate, deduplicate, and enrich web data into useful reports or CRM-ready records.
Workflow Automation
Connect CRM, email, calendars, documents, and team tools into reliable trigger-to-result workflows.
Calendar & Booking Agent
Qualify prospects, check availability, book meetings, confirm appointments, and handle rescheduling.
AI Marketing Campaigns
Coordinate segmented email, SMS, CRM, and campaign activity with approval and optimization loops.
Memory & Context AI
Recall relevant preferences, conversation history, and workflow rules so each interaction starts informed.
AI Receptionist
Answer inbound calls, qualify intent, book appointments, transfer hot leads, and log conversations.
Review Request Agent
Send timely, personalized review requests and route negative feedback into a private recovery workflow.
Lead Follow-Up Agent
Respond to inbound leads quickly, answer questions, qualify intent, nurture, and book next steps.
Appointment Reminder
Send scheduled reminders and keep confirmations, cancellations, reschedules, and calendars synchronized.
Lead Generation Agent
Find and enrich prospects, assess fit, personalize outreach, follow up, and route qualified replies.
API & Integration Layer
Authenticate, validate, transform, and route events between proprietary tools and third-party platforms.
Automated Reporting
Collect business data on a schedule, validate it, analyze results, and deliver useful summaries.
Websites & Landing Pages
Create clear, mobile-first pages that explain the offer, capture leads, and connect to automation.
AI Email Outreach
Research each lead, find relevant hooks, draft tailored messages, classify replies, and follow up.
Featured project
ClawBridge Codex
A self-hosted, multi-channel AI agent platform built around isolated execution, host-side credentials, persistent memory, and an architecture clients can inspect.
Architecture overviewhost → agent → result
InputMessaging, email, CRM, schedules
Control planeRouting, credentials, policy, memory
ExecutionIsolated agent container + bounded tools
How projects move
A clear path from bottleneck to working system.
Clients always know what is being built, what it connects to, how it is tested, and what they will own at handoff.
Map the real work
Clarify the people, tools, data, bottleneck, and required result.
Design the boundaries
Define triggers, decisions, tools, memory, approvals, and failure paths.
Ship the useful core
Create the smallest end-to-end system that proves the workflow.
Test, document, own
Validate realistic scenarios and hand over an operable system.
Memory & context AI
Useful context without exposing the wrong data.
Host-side memory recalls only relevant context before a turn, retains useful outcomes after delivery, and keeps credentials outside agent sandboxes.
Hindsight / host-sidebounded context
L1
Recall before action
Query the correct memory bank and inject only context relevant to the current task.
L2
Retain after delivery
Store useful summaries, preferences, decisions, and business facts after the result is delivered.
L3
Reflect and consolidate
Merge redundant memories, promote important facts, and prune stale or low-value context.
Credential-safe boundaryAgents receive context—not raw secrets or unrestricted memory stores.
Goals, offers, and brand voice
Preserve stable business context without rebuilding the brief every time.
Signals, pain points, and history
Support more relevant qualification, outreach, and follow-up decisions.
Behavior, rules, and integrations
Keep the system aligned with documented workflow and tool boundaries.
Messages across work surfaces
Connect the useful thread across email, chat, CRM, and other channels.
Campaigns, replies, and timing
Avoid repetitive messages and keep bounded follow-up sequences consistent.
Approvals and do-not-contact rules
Retain the constraints the system must respect—not only facts it can use.
Technical stack
Tools selected around the system—not the trend.
The stack spans agent runtimes, code, memory, channels, integrations, infrastructure, and the quality controls needed to operate them.
Agent platforms
- ClawBridge
- ClawBridge Codex
- OpenClaw / Hermes-Agent
- Claude / Codex agents
Runtime & code
- TypeScript / Node 20
- Codex CLI
- Bun agent runner
- Python automation
Memory & data
- Hindsight
- Postgres / pgvector
- SQLite session databases
- Semantic recall / reflect
Channels
- Telegram
- Discord / Slack / Teams
- Linear / GitHub / Email
Integrations
- MCP
- Chat SDK
- Google Workspace
- HubSpot / GoHighLevel
Outreach
- Resend email
- Lead website research
- AI personalization
- Follow-up sequences
Infrastructure
- Docker isolation
- VPS / Mac Mini
- launchd / systemd
- Traefik / SSL
Quality
- pnpm
- Vitest
- ESLint / Prettier
- Health checks / doctor
Built for clarity
Professional AI without the mystery layer.
The model is only one part of the system. Ownership, permissions, observability, and a useful client experience matter just as much.
TypeScriptNode.jsDockerMCPOpenClawHindsightAPIsCRM
Outcome first
Start with the business result and use AI only where judgment adds value.
Human control
Use approvals, escalation, and clear limits for consequential actions.
Client ownership
Favor reviewable code, documented infrastructure, and an explicit handoff.
Evidence over claims
Show architecture, public source, tradeoffs, and limitations clients can inspect.
Start with the workflow
What does your team keep doing by hand?
Describe what happens today, where it slows down, and what a successful result should look like.