Noetis Purchase Research · Personal engine for app builders
Product Comparison Engine for Apps
Compares products on stated needs and total cost of ownership.
Answers: "Can an app compare products against a user's criteria?" For individuals making a considered purchase.
No live prices or availability. It uses only the product details supplied.
Available today
ImplementedImplemented: runs on the shared runtime with supplied material. One bounded development check on 2026-10-12 took 122.5s with 15 model calls and ended "incomplete". That is a development signal, not an evaluation. Customer access is by approved account.
What you send
- Question
- Supplied text material
- Text material up to 150,000 characters per run
What comes back
- Sourced purchase comparison with ownership costs.
- Findings with the located quote and a support status from claim review
- Release status: released, incomplete with reasons, or failed
- Executed roles, usage and measured cost
Sample
Authored illustration. Written by Encevra to show the workflow. Not customer data and not a recorded model output.
Which laptop should I buy for video editing?
Budget $1,800. Laptop A: $1,650, 16GB RAM, 512GB, 2 year warranty. Laptop B: $1,750, 32GB RAM, 1TB, 1 year warranty, review says "fans are loud". Seller claims A is "best for creators".
- Products compared on the user's criteria using supplied details
- Criteria the supplied details do not cover
- Questions to check before buying
The real response shape is documented in the API reference.
How the workflow operates
Each role is a responsibility in the workflow, served by a third party language model. More roles are not automatically better; depth and routing decide which run.
Built with
Models this engine uses: OpenAI (GPT), Anthropic (Claude). Specialists run on OpenAI models and the claim review and final brief on Anthropic models. If a provider has a temporary failure, the step can fall back to an OpenAI model, and the run records that.
Needs Analyst
Define the requirements and their priority.
Product Researcher
Extract product facts from supplied material only.
Cost Analyst
Calculate ownership cost from supplied figures, showing operands.
Evidence Reviewer
Check marketing claims against supplied evidence.
Comparison Analyst
Explain the tradeoffs between the options.
Evidence and deployment
Evidence
This engine reads the text you send in the request. Each released finding carries the exact quote and its character span in that text, located mechanically before release. Quotes that cannot be located are labelled Insufficient evidence and never shown as source verified. Interpretation is reviewed as a separate step, and gaps such as a missing clause describe what was searched instead of citing text that is not there.
Deployment
Runs on Encevra hosted infrastructure using the third party models listed above. Every model call and fallback is checked against the deployment policy first. Private cloud and air-gapped deployment are planned; discuss deployment requirements.
What it does not handle
- Live prices or stock (retrieval not built; analysis is limited to supplied information)
- Authorized source retrieval is not available: Not built. Engines read only supplied material.
- Uses only supplied material. No freshness guarantee beyond the documents provided.
- Required for every output during trials.
How to integrate
Send "engine": "purchase-research" with your question and material from your server. Keys stay server side.
How to evaluate it
No published result for this workflow yet. Build a small answer key from your own work and compare against a strong single model baseline. See the evaluation checklist and method.
Cost and rights: pricing and licensing. Showing outputs to your own customers needs a written agreement.
Related engines
Content reviewed 2026-10-12 by the Encevra engine team. Engine version 0.1.0 on noetis-core-1.