How We Build · A2A · MCP · Google ADK

Production agents,
engineered — not prompted.

Anyone can wire up a chatbot. We engineer agents that hold up in production — specialists coordinating over the open A2A protocol, reaching your systems through MCP, on Google's ADK, with security and human control designed in.

5-layer

Clean agent architecture

Every write

Pauses for human approval

100%

Of actions audited

The same production standard we build every Alis Build platform on.

Multi-agent orchestration

One orchestrator. A team of specialists.

An orchestrator agent plans the work and delegates to purpose-built specialists over A2A — each reaching only the systems it's authorized for, on your behalf.

Gemini Enterprise · ChatResearch agentDocument agentRecruitment agentOperations agentVertex AI SearchYour systemsMCP · toolsOrchestrator
Designed for security, control, and multi-agent orchestration

Blueprints we ship

De-identified agent patterns from real engagements — described by capability, never by client.

Blueprint 01 · Research & Analysis

An analyst that reads everything, and cites it.

Grounds every answer in your private knowledge base, ingests documents, meetings and chats, and runs deep multi-source research into a finished, cited report.

  • Vertex AI Search (RAG) grounding — citations, never guesses.
  • Parallel specialist sub-agents converge on one report.
  • Plan-first — you approve before a long job runs.
Analysts spend time on judgement, not gathering
Cited answer
Revenue grew 18% YoY, driven by the new segment (p. 14) and margin expansion in H2 (meeting · Apr 3).
vault · 6 sourcesweb · 3meetings · 2
Recruitment agent
● awaiting approval
Shortlist 4 candidates for Senior Go Engineer — matched on GitHub activity + LinkedIn profile.
ApproveEdit
Blueprint 02 · Recruitment

Sources, screens, and shortlists — you decide.

Connects to LinkedIn and GitHub to source and understand candidates, scores applications against each role, and runs your pipeline with a locked-down public assistant for applicants.

  • Reads public GitHub to gauge real, published work.
  • LinkedIn sourcing + existing-profile review.
  • Per-tool permissions; anonymous public apply-flow.
Faster shortlists, every action logged
Technical spotlight

The agent stack — battle-tested, layer by layer.

A clean separation of concerns is what makes an agent maintainable, secure and swappable. This is the shape of every agent we ship.

Layer 01

Channels

  • Custom web UI
  • Gemini Enterprise
  • API · extension
Layer 02 · A2A

Orchestration

  • Agent cards · /.well-known
  • Tasks · artifacts · SSE
  • Long-running jobs
Layer 03 · ADK

Reasoning

  • Gemini · OpenAI · Anthropic
  • Planning · budget guards
  • Human-in-the-loop
Layer 04 · MCP

Tools

  • Per-tool IAM
  • Argument validation
  • Sandboxed code exec
Cross-cutting

Security

  • Forwarded identity
  • Zero-trust · mTLS · OIDC
  • Immutable audit trail
Cross-cutting

Governance

  • Visualize every agent
  • Per-user OAuth
  • Searchable audit
Cost & value · You stay in control

See — and control — what every agent costs.

AI is only worth it if the value beats the spend. Every agent we build reports its own usage, so you can watch cost per agent in real time, cap it with budgets, and judge it against the work it returns — you decide what's worth running.

  • Cost broken down per agent, per user, per model — no mystery bill.
  • Set budgets and alerts; agents stop at the ceiling you choose.
  • Weigh spend against value delivered — hours returned, work shipped.
  • Your cloud project, your model keys — the spend is yours, visible and controlled.
Agent usage · this month
$123.54
62% of budget
Research agent$48.20
Document agent$32.60
Recruitment agent$27.40
Operations agent$15.34
Monthly budget$123.54 of $200.00
≈ 120 hours of work returned this month — you decide if it's worth it.

Start your AI journey today.

A discovery call, a scoped pilot on your cloud, then a governed agent your team actually trusts.

See the agents we build