Integrated Reasoning is live · custom pricing · last verified 31 Oct 2026 · viability monitor
Integrated Reasoning
Custom silicon for combinatorial optimization — IRX-Honu targets subset sum and NP-complete decision problems with purpose-built hardware.
A genuinely specific hardware bet: 7,000x on the decision formulation of subset sum is a claim you can test, and that's rare in optimization marketing. The catch is equally specific — evaluation runs on an FPGA-accelerated prototype, not shipping silicon, and the public trail has been quiet since 2023. Shortlist it only when one narrow, hard instance class dominates your runtime and you have hardware people to integrate.
Verdict generatedVerified 4d ago · liveness 47/100 · cite: rightaichoice.com/tools/integrated-reasoning
- Research labs working on NP-complete algorithms who can co-develop against an FPGA prototype
- Enterprise optimization engineers whose runtime is dominated by hard, narrow instance classes
- Cryptography researchers dealing with hard subset sum instances
- HPC specialists with persistent combinatorial kernels they can't push further in software
- Teams that need an off-the-shelf software solver they can license and run today
- General-purpose application development or mainstream software engineering
- Small-scale or hobbyist projects without the instance volume to justify custom hardware
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Skip Integrated Reasoning if you need a solver you can license and run today on ordinary hardware, or if your bottlenecks are spread across general workloads rather than concentrated in hard subset sum instances.
Custom silicon engagements rarely stop at the part — expect to budget engineering time for pipeline integration, since IRX-Honu is designed to sit inside an existing system rather than replace a library call.
Integrated Reasoning engages customers directly, so cost scales with the scope of a bespoke silicon and prototype engagement rather than a per-seat or per-call subscription. That puts it in a different budget conversation than a licensed software solver like Gurobi or CPLEX, which you can trial at low cost, and closer to a custom hardware program where the upfront commitment is engineering time, not a monthly fee.
In short
Integrated Reasoning — Custom silicon for combinatorial optimization — IRX-Honu targets subset sum and NP-complete decision problems with purpose-built hardware. Best for Research labs working on NP-complete algorithms who can co-develop against an FPGA prototype, Enterprise optimization engineers whose runtime is dominated by hard, narrow instance classes, Cryptography researchers dealing with hard subset sum instances. Pricing is on request (custom quotes).
What is Integrated Reasoning?
Integrated Reasoning — Custom silicon for combinatorial optimization — IRX-Honu targets subset sum and NP-complete decision problems with purpose-built hardware. Best for Research labs working on NP-complete algorithms who can co-develop against an FPGA prototype, Enterprise optimization engineers whose runtime is dominated by hard, narrow instance classes, Cryptography researchers dealing with hard subset sum instances. Pricing is on request (custom quotes).
Integrated Reasoning designs high-throughput processors aimed at combinatorial optimization — subset sum, scheduling, routing, resource allocation — the NP-complete class where software solvers hit a wall. Its flagship microarchitecture, IRX-Honu, is pitched as the first built expressly to remove the bottlenecks that show up in practical optimization workloads, with memory access patterns and instruction sequences matched to the problems those workloads actually generate. The headline claim is narrow and testable: IRX-Honu solves the decision formulation of the subset sum problem 7,000x faster than state-of-the-art software, per the company. This isn't a faster solver on a CPU or an algorithm emulated on an FPGA — the pitch is a purpose-built processor plus a custom instruction set, with hardware and algorithms designed in tandem rather than one retrofitted to the other. What you can actually evaluate today is an FPGA-accelerated prototype ahead of full silicon. Integrated Reasoning came out of Y Combinator's Summer 2022 batch and was named among the biggest moonshots in that batch in TechCrunch coverage by Kyle Wiggers. The company engages customers directly rather than selling a downloadable product, which fits a hardware co-development relationship more than a self-serve purchase. That shapes the buyer: labs, cryptography groups, supply chain and logistics teams, and HPC specialists who already know where their bottleneck lives and need hard instances off software. The gap versus a mature solver like Gurobi or CPLEX is maturity, not ambition. Public updates have been sparse since a 2023 news post.
Key features
- IRX-Honu custom microarchitecture built for NP-complete problems
- Solves the decision formulation of subset sum 7,000x faster than state-of-the-art software, per vendor
- Memory access patterns matched to combinatorial optimization workloads
- Instruction sequences tailored to optimization rather than general computing
- Custom instruction set built for optimization workloads
- Organic architecture design pairing hardware and algorithms
- High-throughput processors for complex decision-making
- Targets subset sum, scheduling, routing and resource allocation problems
- FPGA-accelerated prototype available as the evaluation path ahead of full silicon
- Company handles customer engagement directly for serious evaluations
- Aimed at practical applications rather than benchmarks
Behind the verdict
Most optimization vendors sell you a faster solver. Integrated Reasoning is selling you a different machine, and that changes the evaluation entirely. We'd reach for it when a single narrow instance class — hard subset sum, say — dominates your runtime and software has plateaued. In that scenario, a 7,000x figure on the decision formulation is worth the conversation, because it is specific enough to reproduce or contradict. Pick it if you have hardware integration capability and an appetite for co-development. The FPGA-accelerated prototype is the real product today, so your team needs to be comfortable working against an eval platform rather than a licensed binary. That's a research or HPC relationship, not a procurement you finish in a quarter. Pass if you need something you can license and run today. A mature solver like Gurobi or CPLEX stays the safer production call until silicon ships and benchmark numbers get independently reproduced. The gap is maturity, not ambition. Where it bites: the public record is thin. The most recent news item on the vendor site is dated 08.10.2023, and the rest of the page leans on 2022 Y Combinator coverage. That doesn't mean nothing is happening — it means you'll learn the current state of silicon progress in a direct conversation, not from a changelog. One more caveat. The 7,000x number is scoped to the decision formulation of subset sum, not to scheduling or routing broadly. If the problem that hurts you is a TSP variant or a vehicle routing instance, ask pointedly how the architecture maps before assuming the headline carries over.
Limitations
- Public material is early-stage and narrow.
- The 7,000x speedup is stated for the decision formulation of the subset sum problem specifically, with no equivalent figures published for the other optimization domains the company names.
- What can be evaluated today is an FPGA-accelerated prototype rather than deployed silicon, and IRX-Honu is built for sustained throughput on optimization workloads rather than general-purpose computing, so it must be integrated into an existing pipeline.
- The company controls engagement directly, so how much technical detail is available before a conversation is up to them.
as of 2026-10-12
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Is Integrated Reasoning still active?
Integrated Reasoning is live · custom pricing · last verified 31 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Integrated Reasoning? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about Integrated Reasoning?
What people actually say about Integrated Reasoning — is it worth it?
We scanned public community sources for Integrated Reasoning on Nov 3, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 3 of the posts we fetched could be positively tied to Integrated Reasoning. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about Integrated Reasoning — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 31 Oct 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified Integrated Reasoning 12 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed summary, description, our verdict
- — changed who it suits, who should skip it, description, our verdict, summary
- — changed limitations
- — changed who it suits, switching out, who should skip it, setup time, pricing fit, our verdict, use cases, features, hidden costs, summary, limitations, description, switching in
- — changed who should skip it, features, summary, who it suits, our verdict, description
- — changed use cases, who it suits, description, our verdict, features, hidden costs, limitations, switching in, switching out, who should skip it, pricing fit, setup time, summary
Showing the 6 most recent of 12 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Integrated Reasoning cost in 2026?
Integrated Reasoning: Pricing is on request (custom quotes). Pricing last verified 31 Oct 2026.
Where the pricing makes sense
The company stage and team size where Integrated Reasoning's pricing actually pencils out — and where peers do it cheaper.
Integrated Reasoning engages customers directly, so cost scales with the scope of a bespoke silicon and prototype engagement rather than a per-seat or per-call subscription. That puts it in a different budget conversation than a licensed software solver like Gurobi or CPLEX, which you can trial at low cost, and closer to a custom hardware program where the upfront commitment is engineering time, not a monthly fee.
Has Integrated Reasoning's pricing changed?
No plan price for Integrated Reasoning has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Integrated Reasoning?
Pick Integrated Reasoning if you are Research labs working on NP-complete algorithms who can co-develop against an FPGA prototype, Enterprise optimization engineers whose runtime is dominated by hard, narrow instance classes, Cryptography researchers dealing with hard subset sum instances, HPC specialists with persistent combinatorial kernels they can't push further in software.
Look elsewhere if you are Teams that need an off-the-shelf software solver they can license and run today, General-purpose application development or mainstream software engineering, Small-scale or hobbyist projects without the instance volume to justify custom hardware, Buyers without hardware integration capability or appetite for a co-development relationship.
Skip it if Skip Integrated Reasoning if you need a solver you can license and run today on ordinary hardware, or if your bottlenecks are spread across general workloads rather than concentrated in hard subset sum instances.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Integrated Reasoning actually fits — and what changes day-one when you adopt it.
You have a corpus of hard subset sum instances that software solvers chew through for hours. You start on the FPGA-accelerated prototype and benchmark IRX-Honu against your existing solver on the same instances.
Outcome: You get a like-for-like comparison on your own data before any silicon commitment, and a concrete basis for a grant or procurement case.
Your solver spend is dominated by one narrow class of NP-hard routing constraints that keeps queues backed up. You identify that class as the candidate for hardware acceleration rather than the whole model.
Outcome: The narrow, high-volume instance class is the part worth moving off software, which keeps the scope of the engagement bounded and the integration surface small.
You have a pipeline that already runs at scale and a bottleneck you can name. You work with Integrated Reasoning to map IRX-Honu onto that pipeline rather than rewriting the surrounding software.
Outcome: A hardware-in-the-loop setup that targets the kernel, with the rest of your stack untouched.
Use cases
- Run subset sum decision problems 7,000x faster than software on hard cryptographic instances
- Take supply chain routing models with NP-hard constraints off software solver queues
- Accelerate scheduling for manufacturing and logistics where solver time is the bottleneck
- Push resource allocation in network optimization toward real-time throughput
- Do hardware-in-the-loop research on new algorithms for NP-complete problems
- Evaluate the IRX-Honu approach on an FPGA-accelerated prototype before committing to silicon
Setup time & first value
How long it actually takes to get something useful out of Integrated Reasoning — broken out by persona, not the marketing-page minute.
Because IRX-Honu is engaged directly and evaluated on an FPGA-accelerated prototype, first value depends on scoping your instance class and integrating hardware into an existing pipeline — expect a co-development timeline measured in engineering effort, not a same-day install. Teams without hardware integration capability will take meaningfully longer than labs that already run FPGA or
Switching to or from Integrated Reasoning
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a software solver on hard subset sum instances: benchmark the decision formulation of your instances on the IRX-Honu prototype against your current solver before moving any production traffic.
- →From FPGA emulation of optimization algorithms: IRX-Honu is a purpose-built microarchitecture rather than an emulated algorithm, so the port is a re-implementation of the kernel rather than a recompile.
- →From a general-purpose CPU cluster: keep the CPU path for the rest of the pipeline and offload only the narrow instance class that hardware acceleration actually targets.
- ↗To Gurobi or CPLEX: if your bottlenecks turn out to be broad rather than concentrated in hard subset sum instances, a licensed software solver covers more problem classes with far less integration work.
- ↗To an in-house FPGA accelerator: if you need to keep the optimization kernel inside your own team's toolchain, a bespoke FPGA build avoids depending on an external hardware program.
Resources & guides
Tutorials & Learning
GMAT IR 101 | Everything to know about GMAT Integrated Reasoning | Data Insights | Pratik Joshi
Pratik Joshi
GMAT IR Essentials! (Integrated Reasoning Intro)
Cognify GMAT
Master the GMAT: Integrated Reasoning Explained
Definition Discovery
YouTube returned 6 videos for “Integrated Reasoning”, and we withheld 1: 1 did not mention Integrated Reasoning. Showing the 5 we can prove are about Integrated Reasoning.
Official links
What are the best Integrated Reasoning alternatives?
The closest alternatives to Integrated Reasoning we list are Rebellions, Zettascale and Etched AI. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Rebellions | Contact Sales | Custom pricing | — |
| Zettascale | Contact Sales | Custom pricing | — |
| Etched AI | Contact Sales | Custom pricing | — |
Alternatives to Integrated Reasoning
View all
Rebellions
Rebellions builds chiplet-based AI inference hardware — Rebel100 silicon, RebelCard, RebelServer, RebelRack and RebelPOD for enterprise LLM
Zettascale
Zettascale builds XPU accelerator chips that cut AI inference and training energy by keeping data close to compute.
Tools that pair well with Integrated Reasoning
Common stack mates teams adopt alongside Integrated Reasoning, with the specific reason each pairing earns its keep.
Rebellions
Rebellions builds chiplet-based AI inference hardware — Rebel100 silicon, RebelCard, RebelServer, RebelRack and RebelPOD for enterprise LLM
Zettascale
Zettascale builds XPU accelerator chips that cut AI inference and training energy by keeping data close to compute.
Etched AI
Etched builds custom inference silicon and rack-scale frontier inference clusters for trillion-parameter MoE prefill and decode.
Integrated Reasoning vs its closest rival
Integrated Reasoning's closest head-to-head is with Spider Cloud.
Our Integrated Reasoning vs Spider Cloud verdict written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Head-to-head comparisons
Frequently asked questions
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For makers of Integrated Reasoning
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