Axiora vs Bonnard: Which is Better in 2026?
A comprehensive comparison of Axiora and Bonnard covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Axiora if:
- →You need every figure links back to the official filing and document id it came from or entity resolution across kanji, katakana and latin name variants and spvs
Choose Bonnard if:
- →You want more affordable paid plans (from $149/mo)
- →You need per-tenant isolation and role-scoped access built in — unlimited tenants on every plan or oauth 2.1 and idp integration with workos, clerk or okta
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Axiora vs Bonnard: At a Glance
Pricing Comparison: Axiora vs Bonnard
Understanding the pricing differences between Axiora and Bonnard is crucial for making the right choice. Here's how their plans compare side by side.
Bonnard Pricing
💡 Pricing takeaway: Both Axiora and Bonnard offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Axiora and Bonnard stacks up.
What Makes Each Tool Unique
🔵 Unique to Axiora
Features available in Axiora but not in Bonnard:
- ✓Every figure links back to the official filing and document id it came from
- ✓Entity resolution across kanji, katakana and Latin name variants and SPVs
- ✓Activist tracker, unwinding scoreboards and accumulation trajectories
- ✓MCP server exposing 40+ tools for AI agents
- ✓Typed Python SDK and OpenBB Workspace integration on every tier
- ✓Webhook filing alerts and bulk Parquet export on higher tiers
🟣 Unique to Bonnard
Features available in Bonnard but not in Axiora:
- ✓Per-tenant isolation and role-scoped access built in — unlimited tenants on every plan
- ✓OAuth 2.1 and IdP integration with WorkOS, Clerk or Okta
- ✓Connects to dbt, Cube, dbt Semantic Layer, AtScale, LookML or raw warehouse SQL
- ✓Interactive charts generated from the agent's actual query, not a static render
- ✓Agent-friendly tooling: row caps, type hints, structured error responses
- ✓Open-source charting layer usable with any MCP server
Use Case Recommendations
Best for: Axiora
Axiora is a financial data API for Japanese equities where every figure traces back to the source filing it came from, so analysts can cite their work and AI agents can compute instead of guess. Its hardest problem is entity resolution. Japanese disclosure has no common identifier linking a holder across filings: the same investor files through funds, SPVs and offshore vehicles, and the names drift across kanji, katakana and Latin script, so in the public record each vehicle looks like an unrelated small holder. The worked example the company publishes is Toyo Engineering (6330), where sixty separately-filed names resolved to one holder and revealed a coordinated −28.48 percentage-point exit — a stake unwound from 32.72% to 4.24% across fourteen amendments, with the source document ids listed so you can check it. Coverage spans annual, semi-annual and quarterly reports, filing sections with translations, time-series with growth and CAGR, screening, rankings and comparison, company search, ratios and sectors, a filing list and calendar, health scores, buybacks, shareholdings above the 5% disclosure threshold, board composition and AGM voting, and earnings actuals and forecasts. The ownership-intelligence layer adds accumulation trajectories, an activist tracker, unwinding scoreboards, a capital-allocation classifier, a subsidiaries and relationship graph and a per-row purpose audit bundle. Developer surface is strong: an MCP server exposing 40+ AI tools, a typed Python SDK, OpenBB Workspace integration and webhook filing alerts.
Ideal use cases:
- •Teams or individuals who need every figure links back to the official filing and document id it came from
- •Teams or individuals who need entity resolution across kanji, katakana and latin name variants and spvs
- •Teams or individuals who need activist tracker, unwinding scoreboards and accumulation trajectories
- •Teams or individuals who need mcp server exposing 40+ tools for ai agents
- •Anyone focused on financial-data workflows
- •Anyone focused on api workflows
Best for: Bonnard
Bonnard is a platform for shipping customer-facing MCP servers over your own data, which is a narrower and harder problem than building an internal one. An internal MCP server can trust its single caller; a customer-facing one has to isolate each tenant, scope access by role, integrate with whatever identity provider the customer runs, and survive being pointed at by an agent that will happily ask for a million rows. Bonnard supplies that layer pre-built: OAuth 2.1, IdP integration with WorkOS, Clerk or Okta, per-tenant isolation, role-scoped access, observability and rate limiting, on top of SQL querying and semantic-layer querying. It connects to dbt, Cube, the dbt Semantic Layer, AtScale or LookML if you have a semantic layer, and to raw warehouse SQL if you do not. The part that distinguishes it from a plain endpoint is what happens around the answer: interactive charts generated from the agent's actual query rather than a static image, with row caps, type hints and helpful error responses designed for how agents behave when they get something wrong. Dashboard presets and bundled skills ship with it, and the charting layer is released as open source usable against any MCP server. The result is a full BI experience inside Claude or ChatGPT.
Ideal use cases:
- •Teams or individuals who need per-tenant isolation and role-scoped access built in — unlimited tenants on every plan
- •Teams or individuals who need oauth 2.1 and idp integration with workos, clerk or okta
- •Teams or individuals who need connects to dbt, cube, dbt semantic layer, atscale, lookml or raw warehouse sql
- •Teams or individuals who need interactive charts generated from the agent's actual query, not a static render
- •Anyone focused on mcp workflows
- •Anyone focused on business-intelligence workflows
📊 Other Data & Analytics Tools to Consider
Axiora and Bonnard aren't the only options. Here are other popular tools in the same space:
Databricks AI
Enterprise AI and data lakehouse platform
Akkio
No-code predictive AI for business analysts
Hex
Data workspace with AI analysis and apps
MindsDB
AI layer for databases with SQL ML
Obviously AI
No-code ML platform for predictions
Julius AI
Chat with your data for instant analysis
Is one of these your tool?
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Frequently Asked Questions
Is Axiora better than Bonnard?
It depends on your needs. Axiora offers 6 key features including Every figure links back to the official filing and document id it came from and Entity resolution across kanji, katakana and Latin name variants and SPVs, while Bonnard provides 6 features including Per-tenant isolation and role-scoped access built in — unlimited tenants on every plan and OAuth 2.1 and IdP integration with WorkOS, Clerk or Okta. Axiora uses a freemium model with a free tier, while Bonnard is paid with free access available. Choose based on which features and pricing model align with your requirements.
Is Axiora cheaper than Bonnard?
Bonnard is cheaper, starting at $149/month compared to Axiora's $199/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Axiora and Bonnard together?
Yes, many users combine Axiora and Bonnard in their workflow. Axiora excels at every figure links back to the official filing and document id it came from, while Bonnard shines with per-tenant isolation and role-scoped access built in — unlimited tenants on every plan. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Axiora and Bonnard?
While both are data & analytics tools, Axiora emphasizes every figure links back to the official filing and document id it came from, whereas Bonnard is known for per-tenant isolation and role-scoped access built in — unlimited tenants on every plan. The best choice depends on your specific workflow and feature priorities.
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