Seattle’s AI Agent Stack for Teams Around UW, Amazon, and Microsoft

People who learned to ship software around this city’s large employers already know how to call a model. They still end up with a different login for data, another for the agent run, and a laptop for the script. SandBase collapses that:

• 2,000+ models and data APIs across 100+ platforms, paid from a single balance
• Agents you keep and Sessions you start, in the OpenAI Agents and OpenAgentCore shapes
• An E2B-compatible sandbox for files and commands the agent creates
• SKILL.md, so a coding assistant can find those tools instead of a hand-built list

Agents and sandboxes can start with no charge. Eligible data APIs share 100 free calls per day per organization, and that allowance resets at 00:00 UTC. Model tokens are a separate charge—open the listing before a long run.

The endpoint is https://api.sandbase.ai/v1. Authorize with Authorization: Bearer $SANDBASE_API_KEY.

These sources describe the city. They are not a SandBase address.

• Startup Genome’s 2026 Global Startup Ecosystem Report says Seattle moved up to the #10 position, and credits a strong AI-native sub-sector.
• The Paul G. Allen School at the University of Washington says it educates innovators and does research in the Paul G. Allen Center and the Bill & Melinda Gates Center. Its site quotes Microsoft co-founder Paul G. Allen.
• Ai2, the Allen Institute for AI, says it was founded by Paul Allen and partners with the Allen School on foundational and applied work.
• Amazon’s jobs site lists Seattle, Washington as a place it hires.

That is the labor market this page is written for: people who trained or hired here, using one API rather than a new vendor for every tool.

1. Create the shared SandBase API key in the Console.
2. Record an Agent with its model, instructions, and tools through POST /v1/agents or the OpenAI SDK.
3. When projection_status reads ready, start the Session and send the work.
4. Use the E2B SDK at https://sandbox.sandbase.ai if the task needs files or a script.
5. Or give the assistant SKILL.md so it can discover a tool, inspect it, and run it.

Guides: Docs · Agents API · Sandbox quickstart

SandBase’s documented OpenAI Python SDK pattern, with instructions for a Seattle audience.

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["SANDBASE_API_KEY"],
    base_url="https://api.sandbase.ai/v1",
)

agent = client.beta.agents.create(
    model="deepseek/deepseek-v4-flash",
    name="Seattle research brief",
    instructions=(
        "Write for a Seattle product audience familiar with large engineering orgs. "
        "Use more than one source and cite each."
    ),
    metadata={"city": "seattle", "team": "product"},
)

print(agent.id, agent.version)  # agt_..., 1
# Hold the Session until projection_status reads ready.

curl -X POST https://api.sandbase.ai/v1/agents/sessions \
  -H "Authorization: Bearer $SANDBASE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"agent_id": "agt_..."}'

Scripts and files belong in a sandbox. The Sandbox quickstart is the path.

If you looked up an AI agent API Seattle teams can use without dropping the OpenAI Agents SDK, SandBase is that API, with data tools and a sandbox on the same key.

Use these public pages. Do not add a SandBase office, a phone number, or a latency figure for Seattle:

• Startup Genome GSER 2026 — Seattle at #10
• Paul G. Allen School at the University of Washington
• Allen Institute for AI (Ai2)
• Amazon jobs — Seattle, Washington

The ranking sentence is Startup Genome’s. The Microsoft connection on this page is the Allen School’s own line naming Paul G. Allen as Microsoft co-founder, not a claim about a SandBase desk in Redmond. Amazon’s jobs page is the source for Seattle as a hiring location. SandBase does not claim a public Seattle phone number or a city-specific latency SLA on this page.