RAG and agent teams
You need better evidence coverage than vector similarity alone and want to inspect how context was connected.
Typical signal: important context exists across several related chunks or documents.
Design partner programAccepting a small number of pilot conversations
Bring the workload. Help shape the memory layer.
Valori is looking for engineering teams with a real retrieval, agent-memory, or auditability problem. Together, we will define a narrow technical evaluation and measure whether deterministic vector + graph infrastructure improves the system.
Direct founder conversation. No sales handoff and no obligation to publish a logo or testimonial.
A scoped technical evaluation
Built around one real workload
1
Define
Agree on the workload and success criteria.
2
Integrate
Test vector + graph retrieval on representative data.
3
Verify
Inspect retrieval quality, replay, and state evidence.
4
Decide
Continue, pause, or shape the next product milestone.
Current stage
Valori is early. We are looking for design partners, not presenting companies as customers before that is true.
Who it is for
A fit for teams with a hard memory problem
The best design partners already know where ordinary retrieval or opaque state is creating engineering risk.
Regulated or auditable systems
You need to explain what state produced a result, what changed, and whether that state can be replayed.
Typical signal: backups are not enough; the evidence trail matters.
Infrastructure evaluators
You are comparing vector stores, graph retrieval, or deterministic execution for a production workload.
Typical signal: correctness and operational control matter alongside latency.
The engagement
What a design partner receives
This is a collaborative technical evaluation, not a generic product demo or an open-ended consulting project.
Direct founder access
Work with Varshith on architecture, integration questions, and findings without a sales layer.
A scoped pilot
Choose one workload, a representative dataset, and a small number of measurable success criteria.
Retrieval and state evidence
Review vector results, graph-expanded context, replay behavior, and available state proofs.
Roadmap influence
Your real constraints can inform product priorities when they match Valori's core direction.
Pilot structure
A clear path from question to evidence
The evaluation advances only when the previous step produces a useful, reviewable result.
- 01
Fit conversation
Share the workload, current architecture, and the failure mode you want to improve.
Output: A written problem statement. - 02
Success criteria
Choose the dataset, queries, retrieval expectations, and verification requirements.
Output: A bounded evaluation plan. - 03
Technical evaluation
Integrate the workload and compare ordinary vector retrieval with Valori's vector + graph path.
Output: Results and reproducible evidence. - 04
Decision review
Review what worked, what did not, and whether a production relationship makes sense.
Output: A clear continue or stop decision.
Working agreement
Early should still mean professional
A useful design partnership depends on honest constraints, real feedback, and careful handling of data.
No invented endorsement
Your company is never presented as a Valori customer, design partner, logo, or case study without explicit written approval.
Real technical feedback
We want precise feedback on retrieval quality, APIs, operations, and failure modes — including what does not work.
Representative, safe data
Use non-sensitive or properly authorized evaluation data. Production data access is not assumed.
Current status
No customer-logo wall yet — deliberately
Valori is still earning its first public customer stories. Until a team completes a real evaluation and chooses to be referenced, this page will remain a design-partner invitation rather than a collection of unsupported claims.
If you are interested but not ready for a pilot, start with the documentation, inspect the open-source kernel, or read the research paper.
Founder contact
Have a workload worth testing?
Email Varshith with the problem, your current stack, and what a successful evaluation would need to prove. A short technical description is enough to start.
varshith.gudur17@gmail.com