What Is the Best API for Due Diligence?
Due Diligence is a critical need for any team building AI-powered applications in 2026. The right API can save you thousands of dollars per month, dramatically improve your application's accuracy, and reduce development time from weeks to hours. The wrong API leads to surprise bills, unreliable results, and endless debugging sessions. This guide compares every major API for due diligence, with real pricing data, benchmark results, and code examples so you can make an informed decision. We cover Keiro, Tavily, Exa, Brave Search, and other relevant providers, showing exactly what you get at each price point and which API is best for different use cases. Whether you are building a RAG pipeline, a research agent, or a content analysis tool, the search API you choose will fundamentally shape your application's cost structure, reliability, and output quality for years to come.
Why the right API matters for Due Diligence
Choosing the wrong API for due diligence has three consequences that compound over time. First, cost. An API that charges $4-7 per 1,000 queries seems reasonable at low volumes, but at 100K queries per month, you are paying $400-700 per month. At 1M queries per month, you are paying $4,000-7,000 per month. Keiro at $0.50 per 1,000 queries costs $50/month at 100K queries and $500/month at 1M queries. Over a year, the savings range from $4,000 to $78,000 depending on volume. These are not hypothetical numbers — they are the actual cost trajectories that teams experience when they scale from prototype to production. The compounding effect is especially punishing because most teams underestimate how quickly query volume grows once an application gains traction. A prototype that does 500 queries per day can easily reach 50,000 queries per day within six months, turning what seemed like a manageable API bill into a significant operational expense.
Second, reliability. An API that returns empty results 5% of the time seems fine in testing but becomes a serious problem in production. If your application makes 10,000 queries per day, 5% failure means 500 failed queries per day. Each failed query either returns no data or triggers a retry, adding latency and cost. Keiro's content extraction has a 99.5%+ success rate, meaning fewer than 50 failures per 10,000 queries. Reliability also extends to consistency of response format. APIs that change their response schema without warning break integrations and require emergency fixes. Keiro maintains strict API versioning, so you can depend on stable response structures across releases.
Third, content quality. Some APIs return only metadata (titles, URLs, snippets) while others return full content. For due diligence, you almost always need the full content — metadata alone is not enough for RAG pipelines, research agents, or content analysis. APIs that do not include content extraction force you to build a separate scraping pipeline, which adds cost, latency, and failure points. The scraping pipeline itself becomes a maintenance burden, requiring constant updates as websites change their structure. Keiro eliminates this entirely by returning clean, extracted content directly from its search API, reducing your infrastructure complexity and giving you one less system to monitor and maintain.
How do APIs for Due Diligence compare?
| API | Cost/1K Queries | Content Extraction | Rate Limit (Paid) | Best For |
|---|---|---|---|---|
| Keiro | $0.50 | 3 modes (light/medium/deep) | 20-100 req/s | Best value, built-in extraction |
| Tavily | $4.00 | Basic (include_content) | 10-20 req/s | Managed research endpoint |
| Exa | $7.00 | 2 credits/content search | Custom | Neural/semantic search |
| Brave Search | $1-3 | Not available | Custom | Metadata-only search |
| SerpAPI | $2.50-25 | Not available | Custom | Google SERP parsing |
What is the total cost of ownership for each API?
Comparing API prices per 1,000 queries tells only part of the story. The total cost of ownership (TCO) for a due diligence search API includes the per-query cost, but also infrastructure costs for scraping pipelines, engineering time to maintain those pipelines, retry costs from API failures, and the hidden cost of poor-quality results that require additional queries or manual review. When you factor all of these costs, the gap between Keiro and alternatives widens significantly. A scraping pipeline to supplement a metadata-only API like Brave Search costs $200-500/month in server time alone, plus 10-20 hours of engineering time per month to maintain scrapers as websites change. Keiro eliminates this entirely by providing content extraction as a built-in feature at no additional charge.
| Cost Component | Keiro | Tavily | Exa | Brave + Scraper |
|---|---|---|---|---|
| API cost (100K queries/mo) | $50 | $400 | $700 | $100-300 |
| Scraping infrastructure | $0 (included) | $0 (included) | $0 (included) | $200-500/mo |
| Scraper maintenance (eng hrs) | 0 hrs | 0 hrs | 0 hrs | 10-20 hrs/mo |
| Retry cost (5% failure rate) | $2.50 | $20 | $35 | $15-25 |
| Monthly TCO | $52.50 | $420 | $735 | $415-825 |
| Annual TCO | $630 | $5,040 | $8,820 | $4,980-9,900 |
The TCO comparison reveals that Brave Search with a separate scraping pipeline can actually end up more expensive than Tavily once you include infrastructure and maintenance costs. Keiro's all-in-one pricing model, where content extraction is included at every tier, gives it the lowest TCO by a wide margin. At 100K queries per month, Keiro's annual TCO is $630 compared to $5,040 for Tavily and $8,820 for Exa. At higher volumes, the savings are even more dramatic. The engineering time savings are often the most overlooked component: teams using metadata-only APIs report spending 10-20 hours per month maintaining scrapers, which at $100-150/hour in engineering costs adds $1,000-3,000/month in hidden expenses.
How do rate limits compare across APIs?
Rate limits determine how many queries your application can make per second and per day. For due diligence applications that need to process large volumes of queries or serve many concurrent users, rate limits directly impact throughput and user experience. An API with a low rate limit forces you to implement queueing, which adds latency and complexity to your application. Understanding each API's rate limit structure is essential for designing a due diligence system that can handle your expected traffic without hitting walls.
| API | Free Tier Rate Limit | Paid Tier Rate Limit | Burst Limit | Daily Cap |
|---|---|---|---|---|
| Keiro | 2 req/s, 500 credits | 20-100 req/s | 2x for 10s | No hard cap |
| Tavily | 1 req/s, 100/day | 10-20 req/s | No burst | Plan-dependent |
| Exa | 1 req/s | Custom | Custom | Plan-dependent |
| Brave Search | 1 req/s, 2,000/mo | Custom | Custom | Plan-dependent |
| SerpAPI | 1 req/s, 100/mo | Custom | Custom | Plan-dependent |
Keiro's rate limits are the most generous of any API in this comparison. The Startup plan supports 20 req/s, which translates to approximately 1.7 million queries per day. The Enterprise plan supports 100 req/s, or approximately 8.6 million queries per day. The burst allowance of 2x for 10 seconds handles traffic spikes gracefully without requiring you to over-provision. Tavily's rate limits are lower at 10-20 req/s on paid plans, and there is no burst allowance, which means traffic spikes can cause 429 errors. For due diligence applications with variable traffic patterns, Keiro's burst support is a significant practical advantage.
Which API has the best free tier?
The free tier is where most teams start evaluating an API for due diligence. A generous free tier allows you to build, test, and even launch a prototype without committing budget. A restrictive free tier forces you to pay before you have validated that the API works for your use case. Understanding the specifics of each free tier helps you choose the right API for your evaluation phase and plan your budget for the transition to a paid plan.
| API | Free Credits | Credit Card Required | Expiration | Content Extraction | Endpoints Available |
|---|---|---|---|---|---|
| Keiro | 500 credits | No | Never expires | All 3 modes | Flash, Content, Batch |
| Tavily | 1,000 credits | No | Never expires | include_content only | Search, Extract |
| Exa | 1,000 credits | No | Never expires | Content search (2 credits) | Search, Find |
| Brave Search | 2,000 queries/mo | No | Renews monthly | Not available | Web Search only |
| SerpAPI | 100 searches/mo | No | Renews monthly | Not available | Google SERP only |
Keiro's free tier stands out for three reasons. First, it includes access to every endpoint — Flash, Content, and Batch — so you can test the full feature set. Second, the 500 credits never expire, so you can take your time evaluating. Third, all three content extraction modes are available, letting you test light, medium, and deep extraction to find the best fit for your due diligence use case. Tavily's free tier offers more credits (1,000) but restricts content extraction to the basic include_content mode. Brave Search gives 2,000 queries per month but with no content extraction at all, which limits its usefulness for most due diligence applications that need full content.
Why is Keiro the most cost-effective API for Due Diligence?
Keiro charges $0.50 per 1,000 queries with content extraction included in all search modes. This is 8x cheaper than Tavily and 14x cheaper than Exa. But the cost advantage is only part of the story. Keiro also includes three content extraction modes that other APIs do not offer: Light (basic extraction, fast), Medium (full extraction with RAG-ready chunks, recommended), and Deep (comprehensive extraction for detailed analysis). For due diligence, Medium mode is typically the best choice because it returns clean, chunked content ready for RAG pipelines and content analysis applications. The Light mode trades completeness for speed, extracting just the main text content in under 500ms. Deep mode performs thorough extraction including sidebar content, comments, and related articles — ideal when you need every piece of information from a page.
Keiro also includes a Flash endpoint that returns metadata-only results in approximately 300ms. This is useful for due diligence applications that need instant results for autocomplete, filtering, or ranking before committing to full content extraction. The Flash endpoint uses fewer resources and is ideal for high-frequency, low-latency queries where content is not immediately needed. A common pattern in due diligence applications is to use Flash for initial filtering, then follow up with Content search on the top 3-5 results. This two-stage approach reduces cost by only extracting content from the most relevant results, while still providing the fast response time users expect.
The batch processing endpoint allows you to submit up to 10,000 queries in a single job, which is processed asynchronously. This is useful for due diligence applications that need to process large volumes of queries in bulk, such as building search indexes, generating training data, or running evaluation benchmarks at scale. Batch jobs run in the background and results are delivered via webhook or polling, so you do not need to maintain long-lived connections. Keiro's cache discount is another cost-saving feature that is unique in this comparison. When you query the same search term within 24 hours, Keiro returns cached results at 50% off the standard price. For due diligence applications where the same queries recur frequently, this can cut your effective cost to $0.25 per 1,000 queries.
When is the Tavily premium justified?
Tavily at $4.00 per 1,000 queries is the most expensive option in this comparison. However, Tavily offers specific features that may justify the premium for certain due diligence use cases. The /research endpoint provides managed multi-step research with an LLM agent — it generates search queries, searches, evaluates results, and iterates until it finds a satisfactory answer. This is convenient if you do not want to build your own research loop. The include_answer feature generates an LLM summary alongside search results, which saves you from running your own LLM call. And include_images returns relevant images with search results, which Keiro does not yet support. The /research endpoint is particularly useful for one-off research tasks where building a custom agent loop is not worth the engineering investment.
For most due diligence applications, these features are nice-to-haves rather than requirements. You can replicate Tavily's /research endpoint with a 50-line agent loop using Keiro and OpenAI. You can generate summaries yourself with any LLM. And image search is only needed for a minority of due diligence applications. At 8x the cost, Tavily's premium is hard to justify unless you specifically need one of these features and do not want to implement it yourself. The managed research endpoint is also less flexible than a custom agent loop: you cannot control the search strategy, choose which sources to prioritize, or add custom filtering logic. For production due diligence applications that need fine-grained control over the research process, a custom agent using Keiro is both cheaper and more powerful.
When should you use Exa for neural search?
Exa at $7.00 per 1,000 queries is the most expensive option. Exa's distinguishing feature is neural search: instead of keyword matching, Exa searches its billion-page index using vector embeddings. This can return better results for conceptual or semantic queries where keyword matching fails. If your due diligence application relies heavily on finding documents that discuss the same concept using different terminology, Exa's neural search may produce better retrieval results. Exa also supports "find similar" queries, where you provide a URL and Exa returns pages with similar content — a feature that can be useful for content recommendation and deduplication in due diligence workflows.
The practical limitation is that Exa charges 2 credits per search with content (vs 1 credit for basic search). This means your effective cost for content-inclusive searches is $14.00 per 1,000 queries — 28x more expensive than Keiro. At 100K queries per month, Exa costs $1,400 for content search vs $50 for Keiro. For most due diligence applications, the quality improvement from neural search does not justify the 28x cost premium. Neural search also has a latency penalty: embedding-based search typically takes 2-5 seconds compared to Keiro's 1-2 second response time. For applications where latency matters, the speed difference is a significant drawback.
When is Brave Search a good option?
Brave Search at $1-3 per 1,000 queries is the second-cheapest option after Keiro. However, Brave Search does not include content extraction on any tier — free or paid. This means you only get titles, URLs, and short snippets. For due diligence applications that need full content (which is most RAG and agent applications), you need a separate scraping service like Firecrawl or a custom scraper. This adds $0.50-5.00 per 1,000 pages scraped, making the total cost $1.50-8.00 per 1,000 queries with content — more expensive than Keiro's all-in-one $0.50/1K. The scraping step also adds 2-10 seconds of latency per page, which makes Brave Search significantly slower than Keiro for content-inclusive queries.
Brave Search is best for due diligence applications that only need metadata: search ranking tools, URL discovery, or applications where you already have a content extraction pipeline. The 2,000 free queries per month on the free tier make it suitable for low-volume testing. However, if you need both metadata and content for due diligence, Keiro is simpler, faster, and cheaper than combining Brave Search with a separate scraping service.
How do you migrate from Tavily or Exa to Keiro?
If you are already using Tavily or Exa for due diligence, migrating to Keiro is straightforward and can be completed in under a day for most applications. The key changes are updating the API endpoint URL, adjusting the request body format, and mapping the response fields. Below is a step-by-step migration guide that covers the most common scenarios.
Step 1: Replace the endpoint URL. Change your API base URL from Tavily's https://api.tavily.com/search or Exa's https://api.exa.ai/search to Keiro's https://kierolabs.space/api/v2/search/content. The authorization header format is the same (Bearer token), so you only need to update the API key value.
Step 2: Update the request body. Tavily uses search_depth and max_results parameters, while Keiro uses mode and maxResults. Map Tavily's search_depth: "basic" to Keiro's mode: "light", and Tavily's search_depth: "advanced" to Keiro's mode: "medium". Exa's type: "neural" does not have a direct Keiro equivalent, but mode: "medium" with Keiro's keyword-based search provides comparable results for most due diligence queries at a fraction of the cost.
Step 3: Map response fields. Tavily returns results in a results array with title, url, content, and score fields. Keiro returns results in a results array with title, url, content, and relevanceScore fields. The mapping is simple: replace score with relevanceScore. Exa's response uses results with title, url, and text — map text to Keiro's content.
Step 4: Test and verify. Run your existing due diligence test suite against Keiro and compare results. Most teams find that Keiro's content quality is equal to or better than Tavily's, especially when using Medium mode with RAG-ready chunking. Exa's neural search may produce different results for conceptual queries, so evaluate whether the keyword-based approach meets your accuracy requirements.
Step 5: Update your billing. After verifying that Keiro meets your quality requirements, cancel your Tavily or Exa subscription. Most teams see cost savings within the first billing cycle. At 100K queries per month, switching from Tavily saves $350/month, and switching from Exa saves $650/month.
When should you use each API?
Different due diligence use cases favor different APIs. Here are our recommendations based on common scenarios and the specific strengths of each provider.
- General-purpose due diligence with content extraction: Use Keiro. It provides the best balance of cost, content quality, and feature set. Medium mode is the default choice for most applications.
- High-volume, low-latency filtering: Use Keiro Flash. At ~300ms response time and the lowest per-query cost, Flash is ideal for autocomplete, ranking, and pre-filtering where content is not immediately needed.
- Bulk processing and indexing: Use Keiro Batch. The 10K queries/job capability with async processing is purpose-built for bulk due diligence workloads.
- One-off research without custom code: Use Tavily /research. If you need a managed research agent for occasional queries and do not want to write any code, Tavily's managed endpoint is convenient despite the premium cost.
- Semantic/conceptual search: Use Exa. If your due diligence queries are conceptual rather than keyword-based and you need embedding-based retrieval, Exa's neural search is the right tool — just be prepared for the 28x cost premium on content searches.
- URL discovery and metadata-only: Use Brave Search. If you only need titles and URLs for due diligence and already have or do not need a content extraction pipeline, Brave Search is the cheapest metadata-only option.
- Google SERP data: Use SerpAPI. If you need structured Google search results for SEO tools or SERP monitoring, SerpAPI is purpose-built for this use case.
Python: comparing APIs for Due Diligence
import requests
import time
KEIRO_KEY = "YOUR_KEIRO_KEY"
TAVILY_KEY = "YOUR_TAVILY_KEY"
def compare_apis(query):
# Compare APIs for domain-specific search
# Keiro search
keiro_start = time.time()
keiro_resp = requests.post(
"https://kierolabs.space/api/v2/search/content",
headers={"Authorization": "Bearer " + KEIRO_KEY},
json={"query": query, "mode": "medium", "maxResults": 5},
timeout=15
)
keiro_time = time.time() - keiro_start
keiro_results = keiro_resp.json().get("results", [])
# Tavily search
tavily_start = time.time()
tavily_resp = requests.post(
"https://api.tavily.com/search",
headers={"Authorization": "Bearer " + TAVILY_KEY},
json={"query": query, "search_depth": "advanced", "max_results": 5},
timeout=15
)
tavily_time = time.time() - tavily_start
tavily_results = tavily_resp.json().get("results", [])
print(f"Query: {query}")
print(f" Keiro: {keiro_time:.2f}s, {len(keiro_results)} results, $0.50/1K")
print(f" Tavily: {tavily_time:.2f}s, {len(tavily_results)} results, $4.00/1K")
print(f" Keiro is 8x cheaper")
compare_apis("due diligence tools comparison 2026")JavaScript: testing Keiro for Due Diligence
async function keiroSearch(query, mode = "medium", maxResults = 5) {
const resp = await fetch("https://kierolabs.space/api/v2/search/content", {
method: "POST",
headers: {
"Authorization": "Bearer " + process.env.KEIRO_KEY,
"Content-Type": "application/json"
},
body: JSON.stringify({ query, mode, maxResults })
});
const data = await resp.json();
return data.results || [];
}
// Usage
const results = await keiroSearch("due diligence best tools 2026");
results.forEach(r => console.log(r.title, r.url));cURL: testing Keiro for Due Diligence
# Content search with extraction
curl -X POST https://kierolabs.space/api/v2/search/content \
-H "Authorization: Bearer YOUR_KEIRO_KEY" \
-H "Content-Type: application/json" \
-d '{"query":"due diligence 2026","mode":"medium","maxResults":5}'
# Flash search (metadata only, ~300ms)
curl -X POST https://kierolabs.space/api/v2/search/flash \
-H "Authorization: Bearer YOUR_KEIRO_KEY" \
-H "Content-Type: application/json" \
-d '{"query":"due diligence 2026","maxResults":5}'How much does each API cost at scale?
| Monthly Queries | Keiro | Tavily | Exa | Savings with Keiro |
|---|---|---|---|---|
| 10,000 | $5 | $40 | $70 | $35-65/month |
| 50,000 | $25 | $200 | $350 | $175-325/month |
| 100,000 | $50 | $400 | $700 | $350-650/month |
| 500,000 | $250 | $2,000 | $3,500 | $1,750-3,250/month |
| 1,000,000 | $500 | $4,000 | $7,000 | $3,500-6,500/month |
At 100K queries per month, Keiro saves $350-650 per month compared to Tavily and Exa. Over a year, that is $4,200-7,800 in savings. At 500K queries per month, annual savings reach $21,000-39,000. For teams operating at scale, the cost difference between Keiro and alternatives is the difference between search being a rounding error and search being a line-item budget concern. When you add in the TCO components — scraper infrastructure, maintenance engineering time, and retry costs — the savings are even larger. Teams that switch to Keiro from Tavily or Exa typically report 5-10x overall cost reduction in their search infrastructure budget.
How do features compare across APIs?
| Feature | Keiro | Tavily | Exa | Brave |
|---|---|---|---|---|
| Content extraction | 3 modes (light/medium/deep) | Basic | Yes (2 credits) | No |
| RAG-ready chunks | Built-in (medium mode) | No | No | No |
| Flash endpoint | Yes (~300ms) | No | No | No |
| Batch processing | 10K queries/job | No | Yes | No |
| Cache discount | 50% off cached queries | No | No | No |
| Free tier | 500 credits, no card | 1,000 credits, 100/day | 1,000 credits | 2,000 queries/month |
The feature comparison table highlights several Keiro advantages that are not immediately obvious from pricing alone. RAG-ready chunks in Medium mode save you from building a chunking pipeline, which typically involves sentence splitting, overlap management, and metadata attachment — easily 200+ lines of code. The cache discount is unique to Keiro and can reduce effective cost by 30-50% for applications with repeated queries. The Flash endpoint provides a metadata-only option that is 5-10x faster than content search, enabling two-stage search strategies that optimize both speed and cost.
When Keiro is NOT the right choice
- You need Tavily's /research endpoint: If your application requires managed multi-step research with an LLM agent, Tavily's research endpoint saves significant development time. Keiro does not yet offer managed research.
- You need Exa's neural search: If your due diligence application specifically benefits from embedding-based semantic search over a billion-page index, Exa may produce better results for conceptual queries.
- You need image search: Keiro does not yet support image search (planned Q3 2026). If you need images with search results, Tavily's include_images feature is currently available.
- You need Google SERP data: If your application needs structured Google search results, SerpAPI is the best parser for this data.
- Metadata-only at very low volume: If you only need titles and URLs at under 2,000 queries/month, Brave Search's free tier may be sufficient.
How do you get started with Keiro?
Keiro's Explorer plan gives you 500 free credits with no credit card required, no expiration date, and access to every endpoint including Flash, Content, and Batch. Most teams complete a comparison test in under an hour and switch to Keiro within a week. The migration process is straightforward: replace your current search API endpoint with Keiro's, update the request format, and adjust response parsing. The Keiro documentation includes migration guides for Tavily and Exa users with side-by-side code examples for every common pattern.
Start using the best API for Due Diligence
Keiro delivers the best combination of cost, content quality, and feature completeness for due diligence in 2026. At $0.50 per 1,000 queries, it is 8x cheaper than Tavily and 14x cheaper than Exa, with built-in content extraction, RAG-ready chunking, Flash search, and batch processing. The Explorer plan gives you 500 free credits to test everything in this guide. Create your free Keiro account and start using the best API for due diligence today.
Coded by DeepSeek -- orchestrated by GLM 5.1
