Approximate nearest-neighbor search over large vector collections, with recall checked against exact reference queries.
Discuss ANNForgeTHE PRODUCT, IN PRACTICE
A large vector collection creates a trade-off between retrieval cost and how many of the true nearest neighbors are found. ANNForge provides an approximate search path and a reference-based recall check. The useful output is not only a returned neighbor list: it is a result whose retrieval quality can be evaluated at the customer’s dataset, query and resource scale.
Scanning every candidate for every query may not suit the intended vector-search workload.
ANNForge offers an approximate-neighbor path for the supported vector collection, giving the team another retrieval configuration to evaluate.
Query speed alone does not say how well an approximate result matches the true nearest set.
The recall@k checking path compares returned neighbors with exact reference search on the evaluation queries.
Recall, dimensionality, query count and index cost belong to the same deployment decision.
Qualification uses the actual dataset characteristics and query workload to compare retrieval quality, runtime and memory together.
The product scope below describes the capability and outputs to confirm for your release. Custom integration, operated delivery and additional engineering are separately agreed.
Search results for the supported vectors and query set.
The returned approximate nearest-neighbor selections for downstream retrieval use.
A comparison with exact reference neighbors on the qualification queries.
Defined vector dimensions, k, input size and resource requirements for evaluation.
ANNForge is fully available with CLI, MCP and headless access. Use the interface that fits your terminal, your agents or your automated workflow.
Run the product from a terminal or script, alongside the tools your team already uses.
Get CLI accessConnect MCP-compatible clients and agents to the product’s exposed capabilities.
Get MCP accessOperate without a graphical interface in unattended, scheduled or pipeline-driven work.
Set up headless accessProduct-specific inputs, hardware requirements and result guarantees still apply. An access mode does not change your license or deployment scope.
Explore all product interfacesA search team wants to test a different retrieval path without accepting a speed claim that omits quality.
Illustrative use of the supported scope, not a customer case study or a measured result.Choose the supported corpus, queries and requested neighbor count.
Run approximate retrieval and exact reference checks on the evaluation set.
Compare recall, query cost and memory at the same workload scope.
Vector-search, retrieval and data-platform teams evaluating a supported nearest-neighbor workload.
CLI, MCP and headless access are all available. Run from a terminal or script, connect an MCP-compatible client, or use the product without a graphical interface. Choose the mode during onboarding and receive its setup instructions. Runtime requirements and supported operations remain product-specific.
Approximate retrieval is not an exact-neighbor guarantee for every query. The supplied 0.821 recall on five million vectors belongs to its specific campaign settings; production comparisons need the dataset, dimensions and timing scope.
The agreed ANNForge release, its supported interfaces and outputs, the applicable checks and the support stated in your order. The plan defines users, workflow, environment and capacity. Source-code transfer, unrestricted redistribution and bespoke engineering are not automatically included.
Request a scoped engineering or operated-service proposal. It identifies what our team delivers, where the workload runs, infrastructure costs, acceptance requirements and ongoing support. Your software subscription alone does not activate a hosted runtime.
Explore engineeringP47 / Company-reported. The supplied campaign reports recall of 0.821 on five million vectors in 36.85 seconds. The dataset, dimensions, query count, k and timing boundary must accompany any comparison.
These descriptions come from the supplied product and campaign material. Website checks are not an independent rerun of the engine. Qualification identifies the actual release, workload and available artifacts.
Read the evidence summaryCustomer-hosted access and a service operated by SpinForge are different scopes. Confirm the release, deployment and included support before activation.
Plans & deliveryBring a representative workload and the result your team needs. We’ll define the product, deployment and engineering scope around that task.
Activate this capability inside a qualified checked decisions workflow. Compatible methods and required shared checking are included once within that workflow; the product remains independently purchasable.
Capacity, release, environment, result contract and operating responsibilities are specified before activation. Choosing an additional method is not permission to add an unrelated workload or unqualified deployment.
Explore Checked Decisions Choose workflow capacityCommission the model, integration and acceptance work needed for your task. Existing products stay independently available.
Use the software directly or ask us to scope the implementation.
One capability. A connected workflow.
A team to put it into practice.