One platform. Three astrology systems. An in-house astronomical engine. AI interpretation grounded in the classical texts. Here is the evidence, every number verifiable.
No competitor comes close to this surface area. Every bar is a production category you can call today.
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Most APIs do one. Vedika ships all three, fully isolated so values never cross-contaminate between systems.
Vedika does not rent its astronomy. The XALEN Ephemeris is our own engine for planetary positions, house cusps and divisional math — a core differentiator no other astrology API owns.
It delivers sub-arcsecond precision, independently validated against reference ephemerides. That is the foundation every one of the 700+ operations is built on.
XALEN Ephemeris is open-source (Apache-2.0). Below is its measured agreement with NASA's JPL DE440 reference ephemeris across a dense 1900–2050 grid (3,653 epochs per body), in arcseconds of ecliptic longitude. Every number here is reproducible from the public repo with a single command — nothing is hard-coded.
# Fetch NASA's public DE440 kernel, then run the benchmark
curl -L -o /tmp/de440s.bsp https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/planets/de440s.bsp
cargo run -p xalen-validation --release --bin de440_bench| Body | Mean (″) | RMS (″) | Max (″) |
|---|---|---|---|
| Sun | 0.08 | 0.10 | 0.19 |
| Mercury | 0.08 | 0.10 | 0.26 |
| Venus | 0.09 | 0.11 | 0.40 |
| Mars | 0.08 | 0.09 | 0.32 |
| Jupiter | 0.16 | 0.19 | 0.46 |
| Saturn | 0.17 | 0.19 | 0.39 |
| Uranus | 0.40 | 0.56 | 1.41 |
| Neptune | 0.62 | 0.89 | 2.15 |
| Pluto | 0.35 | 0.45 | 1.29 |
| Moon | 2.20 | 2.82 | 11.52 |
How to read it, honestly: every planet agrees with the NASA JPL DE440 reference to sub-arcsecond across the full 150-year window; the analytic Moon is arcsecond-class (load the DE440 kernel for sub-arcsecond Moon when you need it). We match the reference-grade standard — we do not claim to beat Swiss Ephemeris, which is itself a JPL reference. No competitor publishes a comparable runnable benchmark. Source + 2,200+ tests: github.com/vedika-io/xalen-ephemeris · install: cargo add xalen-ephem / pip install xalen / npm i @xalen/wasm.
Astronomy is computed, not guessed. Interpretation is grounded in the texts real astrologers train from.
Measured on the spiritual domain Vedika serves.
Every interpretive claim traces to a recognised classical source — the canon practising astrologers are trained from. No blog summaries, no invented verses.
Built for production traffic with an enterprise uptime SLA.
Computation and AI interpretation return in a single round trip. Response latency is typically 200–800ms, backed by a 99.9%+ uptime SLA across redundant regions.
11 Indian languages and 19 international languages — written by the model, not machine-translated after the fact.
Generic astrology APIs hand you numbers and stop. Vedika returns computation, AI interpretation and precision-checked output in a single call.
| Capability | Vedika API | Generic astrology APIs |
|---|---|---|
| Astronomical computation | In-house XALEN Ephemeris | Third-party / raw values |
| AI interpretation in the same call | Yes, native | No — raw JSON only |
| Positional precision | Sub-arcsecond, validated | Unstated |
| Astrology systems | 3 — Vedic, Western, KP | Usually 1 |
| Total API operations | 500+ | Tens |
| Languages | 30 native | 1–2 |
| Classical-text grounding | BPHS · Phaladeepika · Saravali · Jaimini | None |
| Free keyless sandbox | 130+ mock endpoints | Rare |
| SDKs & integrations | JS · Python · MCP (36 tools) · WordPress | Minimal |
Everything you need to go from signup to production, fast.
700+ operations, three systems, your own white-label astronomical engine behind every call. Start free in the sandbox or get a production key today.