Embedding + Neural Search, Unified

Give your AI agents one coherent voice.

Other platforms hand you an embedding API, a vector store, leaving complex chunking strategies, ranking, and evaluation up to you. Enscrive unifies the entire retrieval pipeline behind a single primitive—Agent Voices—so each agent has one configuration for how it chunks, embeds, retrieves, and improves. Focus and coherence, by design.

Explore the API Install the CLI

Install Enscrive locally · free, no signup

curl -fsSL https://install.enscrive.io/install.sh | sh

Then run enscrive init to bring up the full local stack.

50+ REST Endpoints

8 Embedding Models

3 Geo-Pinned Regions

$0 Local CLI

Available now · free, local-first

The full toolkit on your laptop. No account required.

enscrive-cli is a single static binary that gives you the entire Enscrive workflow locally. Same commands, same JSON shapes as the managed API—so the day you decide to ship to a managed plan, nothing changes except the endpoint.

Install in one line, then enscrive init walks you through bootstrapping the local stack—managed mode against api.enscrive.io, or self-managed mode that pulls service binaries from the same signed distribution.

Ingest, search, voice tuning, eval runs — all local
Same JSON shapes as /v1 — pipe to jq and ship
Bring your own embedding key (OpenAI, Voyage, Nebius) or self-host BGE
macOS, Linux, x86_64 + arm64 — one installer for all

Install & first search

# install — one line, no account, no signup
curl -fsSL https://install.enscrive.io/install.sh | sh

# bring up the full local stack (managed or self-managed)
enscrive init

# spin up a local collection and ingest a directory
enscrive collections create knowledge-base
enscrive ingest knowledge-base ./docs

# search it from your shell
enscrive search knowledge-base "how does onboarding work?" --top-k 5

Prefer to call the cloud directly? The same workflows live on the managed /v1 REST API.

The Choice

Months of infrastructure, or minutes to production.

Your AI agents need persistent memory. You can spend months building it from scratch, cobble together commodity APIs, or point your agents at Enscrive and start shipping today.

A purpose-built memory stack engineered for type-safe retrieval from ingestion to result. Your agents need memory. That's our entire focus.

Option A

Build It Yourself

Select embedding providers, deploy vector storage, design chunking, build ranking, write evals.

3–6 months before product code

Option B

Commodity APIs

One API for embeddings, another for vectors, a third for re-ranking. No coherence between them.

Weeks of integration, ongoing glue

Enscrive

Unified by Voices

Embedding, chunking, ranking, evaluation—one platform, one primitive. A Voice is the whole pipeline as one coherent configuration.

Minutes to first search

The unification primitive

Agent Voices: one configuration for the whole pipeline.

A Voice is how Enscrive collapses chunking, embedding, ranking, and evaluation into a single coherent profile. A support bot Voice is different from a research-assistant Voice—but each one is one object: versioned, diffable, eval-gated, promotable across environments. No more keeping four mismatched configs in sync by hand.

Chunking

How documents are split. Baseline (semantic paragraph), Story Beats (LLM-detected narrative boundaries), or Tone Segments (topic shifts).

Embedding

How chunks become vectors. Pick model, dimensions, and resolution. Adaptive Resolution indexes multiple granularities for routed queries.

Retrieval

How results are ranked. Pure vector, hybrid (BM25 + dense), or adaptive. Tunable thresholds, top-k, and dense/sparse alpha per query.

Start from a template, tune from there.

Four built-in templates cover common patterns. Customize or start from scratch.

General Purpose

text-embedding-3-small · 512 tok

Balanced defaults for most use cases. Start here and tune as needed.

High Precision

text-embedding-3-large · 256 tok

Strict matching, low tolerance for noise. High threshold, small chunks.

High Recall

text-embedding-3-small · 1024 tok

Cast a wide net. Lower threshold, larger context, don't miss relevant results.

Conversational

text-embedding-3-small · 384 tok

Optimized for chat-style queries and short-form questions.

Evaluation, first-class · Professional & Enterprise

Prove what you ship. Then ship what you proved.

Most retrieval platforms hand you a vector store and wish you luck. Enscrive treats evaluation as a first-class primitive: every Voice is measurable against a dataset, every promotion across environments can be gated on the result, and every published score is reproducible.

The evals surface is built around a single /v1/evals/{id} control tower—dataset, target, methodology, runs, diagnose—all from one endpoint. Available on Professional and Enterprise plans; rolling out now.

HuggingFace dataset sampling

Stream BeIR, MTEB, or any HuggingFace dataset by URL. Sample stratified subsets for fast iteration; expand to the full corpus when the Voice is dialed in.

Deterministic + LLM-reasoned sampling

Stratified-random with seed for reproducibility, or LLM-reasoned to surface hard queries first. Same eval, two cost profiles.

Scorers validated against BEIR

nDCG@k, Recall@k, Precision@k, MRR, MAP — all closed-form Rust, validated against published BEIR baselines. No mystery numbers.

Voice-diff with cost estimator

Before promoting a new Voice, see whether the change is query-only (free) or corpus-invalidating (re-embed, with a $ + wall-clock estimate up front).

Public benchmarks coming. Eval runs against canonical datasets (BEIR/fiqa, scifact, hotpotqa) will publish to /benchmarks—reproducible, dated, pinned to a Voice version.

For Developers

Built for developers. Designed for agents.

A complete /v1 REST API, a free local CLI, and a developer portal with an interactive explorer. Every capability reachable from either client—same shapes, same auth, same Voices.

import requests response = requests.post( "https://us.api.enscrive.io/v1/search", headers={"Authorization": "Bearer ens_sk_..."}, json={ "collection": "knowledge-base", "voice": "high-precision", "query": "How does the onboarding flow work?", "top_k": 5 } ) for result in response.json()["results"]: print(f"[{result['score']:.2f}] {result['text'][:120]}...")

Available

/v1 REST API

50+ endpoints covering the complete lifecycle from collection creation to eval-gated Voice promotion.

Collections, voices, documents, chunks
Ingest with SSE progress streams
Semantic, hybrid, and adaptive search
Datasets, evals, runs, benchmarks
Jobs, batch sets, staging & commit
Backups, restore, log streaming

Available

enscrive-cli

The full toolkit as a single static binary. Free on your laptop; same commands and shapes as the managed API. SHA256-verified install from a signed distribution.

curl -fsSL https://install.enscrive.io/install.sh | sh
enscrive init bootstraps managed or self-managed mode
Ingest, search, voice tuning, eval runs
Environment + region switching built in
Static binary, macOS + Linux, x86_64 + arm64

Coming Soon

enscrive-docs

Drop a first-class neural-search /docs endpoint into your existing app. Polished HTML for humans, JSON search for agents.

Markdown directory in, retrieval-native site out
JSON /search + /llms.txt + sitemap
Backed by Enscrive collections + Voices
Single Rust binary, zero runtime deps
docs.enscrive.io →

Platform

Nine capabilities, one memory stack.

Multi-Provider Embeddings

OpenAI, Voyage.ai, BGE, and Nebius — eight models across four providers. Switch without re-architecting.

Hybrid Search

Dense vectors fused with sparse BM25. Tunable alpha across the dense/sparse spectrum, per query.

LLM-Powered Chunking

Beyond fixed-size splits. Story Beats find narrative boundaries; Tone Segments find topic shifts.

SHA256 Change Detection

Fingerprint-based dedup at ingest. Re-upload unchanged documents at zero cost. Pay only for what changed.

Adaptive Resolution

Multi-granularity embeddings: topic, context, precise. Adaptive mode oversamples then re-ranks.

Multi-Environment

Isolated dev, staging, and production scopes. Promote Voices across environments with eval-gated workflows.

Batch Embedding APIs

Routes through OpenAI, Voyage, and Nebius batch APIs by default. ~50% cost reduction on large ingests.

Staging & Commit

Stage, commit, and revert collection mutations with an auditable history. No accidental wipes.

Backup & Restore

Incremental backups and point-in-time restore with dry-run preview. Built-in, not a checkbox.

Privacy · Portability · Trust

Your data, your region, your terms.

Region pinning is a contract, not a hint. Cloud-managed tiers are pinned to the region matching your jurisdiction — no silent cross-region replication, no "eventual" residency, no cross-jurisdiction opt-out. Your data is portable on day one, encrypted in transit, and isolated per tenant by design.

Privacy

Geo-pinned by jurisdiction

US customers in Ohio, EU customers in Frankfurt, APAC customers in Singapore. Pinning is automatic at sign-up — no cross-jurisdiction opt-out on cloud-managed tiers. Vectors, embeddings, and source documents stay in-region for the collection's lifetime. GDPR, Schrems II, APPI — unambiguous.

Privacy

Tenant + environment isolation

Every request is checked against tenant and environment boundaries before it reaches storage. PII (emails, API keys, IPs, bearer tokens) is redacted at the vector pipeline before it ever lands in a log line.

Privacy

Dedicated tenancy (Enterprise)

Enterprise plans run on dedicated Qdrant instances in any of US (Ohio), EU (Frankfurt), or APAC (Singapore) — single-region or multi-region — with optional VPC peering, BYOK / CMEK, and SOC2 Type II reporting. Same API, harder boundary.

Portability

Full export & restore

Incremental backups and point-in-time restore are first-class endpoints, not a support ticket. Export collections, vectors, and Voices as portable artifacts you own and can re-ingest anywhere.

Portability

Open formats & clients

JSONL datasets, BeIR-compatible qrels, plain HTTP + JSON. Both clients (CLI and REST) read and write the same shapes; the local CLI is free forever, so leaving the managed plane never strands you.

Security

HMAC + TLS, audited mutations

Constant-time HMAC-SHA256 API key validation, TLS 1.3 in transit, environment-scoped keys, and stage / commit / revert workflows on every collection change. Auditable by design, not by promise.

Ready to give your agents one coherent voice?

Ship on the managed API today, or run the full stack on your laptop with the free CLI— curl -fsSL https://install.enscrive.io/install.sh | sh.

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