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Deep Research at Scale

Define your schema. Upload thousands of entities. Get validated JSON. Build custom applications.

Parallel processing Schema validation REST API
Live Example

Structured data, ready for your app

Define any research schema, run it on any list of entities, and get clean JSON back—ready to power dashboards, reports, or any application you build.

Markets

Electric Vehicles

Current Size

$396.49 billion

Projected 2030

$620.33 billion

CAGR

7.7%

Market Stage

growth

Market Outlook

Short-term (1-2 years)

1–2 years: Continued global unit growth (IEA and private forecasters expected >20 million EVs in 2025/2026 range in base scenarios), but significant regional divergence. China will continue to lead volumes; Europe will remain policy-driven; North America is sensitive to U.S. federal incentives and tariff/policy shifts. Near-term revenue growth for the sector will be positive but margins under pressure due to price competition and OEM inventory/discounting.

Medium-term (3-5 years)

3–5 years: EV penetration continues to rise materially as battery pack prices decline further and new models reach price parity in many segments. BEVs are likely to represent an increasing share of new-car sales globally, but absolute outcomes depend on policy environment, commodity cycles and trade frictions. Infrastructure and service businesses (charging, fleet services, battery recycling) will capture outsized growth relative to vehicle OEM profits.

Investment Recommendation

Overall positive on multi-year structural growth in EV adoption (market stage: growth). Recommend selective, diversified exposure: prioritize battery-materials and cell manufacturers with scale, charging infrastructure and software/service providers, and OEMs with clear cost advantages or differentiated technology. Be cautious on direct retail/OEM equity exposure in markets with high near-term policy risk (for example, U.S. federal incentive uncertainty) and watch for OEM margin pressure and potential write-down risk (examples: recent GM/EU reporting). Use a multi-theme approach (supply chain + infrastructure + software) to mitigate single-company/policy risks.

Opportunities

  • Invest in battery supply chain and materials (refining, cathode/anode materials, recycling/second-life).
  • Charging infrastructure networks and software/energy services (V2G, managed charging).
  • Fleet electrification solutions and telematics/energy-management software for commercial operators.
  • Selective exposure to low-cost/high-volume OEMs and component suppliers with proven cost advantages.

Key Uncertainties

  • Federal and regional policy changes (notably U.S. EV incentives, tariffs and EU trade remedies).
  • Raw-material and cell supply chain disruptions or sustained commodity price increases.
  • Pace of battery-technology breakthroughs (solid-state commercialization) and commercial scalability.
  • Macro demand (consumer discretionary spending) and conversion to purchase despite improving TCO.
How it works

Research at machine speed

lovelace combines deep AI research with structured data extraction, delivering validated results you can build on.

Batch Processing

Upload CSV, paste a list, or call the API. Research runs in parallel across all entities simultaneously.

2,500 entities / ~45min total

Schema-Defined Output

Design your data structure visually. Every response is validated against your schema.

{ "ceo": "string" }

REST API

Fetch results programmatically. Build dashboards, reports, or integrate into your existing workflows.

GET /api/results

Visualization

Define any research schema, run it on any list of entities, and get clean JSON back—ready to power dashboards, reports, or any application you build.

Apple Inc.
Tesla Motors
OpenAI
Stripe
Anthropic
SpaceX
{
"company_name": "Apple Inc.",
"founded": 1976,
"headquarters": "Cupertino, CA",
"products": [
"iPhone",
"Mac",
"iPad",
"Services"
],
"annual_revenue": "$394B (2024)"
}
INPUTDEEP RESEARCHOUTPUT
Schema-First Design

Define once, extract everywhere

Your schema is the contract. lovelace ensures every research result matches your exact data structure.

schema.json
{
  "company_name": "string",
  "founded": "number",
  "headquarters": "string",
  "products": ["string"],
  "annual_revenue": "string"
}
result.json Validated
{
  "company_name": "Stripe",
  "founded": 2010,
  "headquarters": "San Francisco, CA",
  "products": [
    "Payments",
    "Billing",
    "Atlas",
    "Radar"
  ],
  "annual_revenue": "$14.3B (2023)"
}
Developer-First

Integrate in minutes

Fetch results via REST API. Filter by entity, status, or date. Build dashboards, reports, or power your own AI applications.

Structured JSON responses

Every result matches your schema exactly

Real-time status

Poll for updates or use webhooks

Bulk export

Download all results as JSON or CSV

curl -X GET "https://api.lovelace.dev/v1/jobs/job_123/results" \
  -H "Authorization: Bearer sk_live_..." \
  -H "Content-Type: application/json"
Pricing

Pay for what you research

Usage-based pricing that scales with your needs. Start free, upgrade when you're ready.

Usage-Based

Charged per entity researched. Volume discounts available.

  • Free tier for experimentation
  • No monthly minimums
  • Volume discounts at scale
  • Enterprise plans available

Ready to scale your research?

Join developers building the next generation of research-powered applications.