Constraint Intelligence Platform
Hard constraint decisions before the deadline.
Model + time budget → best verified assignment. Residual violations and provenance included.
Developer access via GitHub Sponsors — purchase API credits at 1.5× your sponsorship amount.
Distinct campaigns — open the evidence ledger.
Why teams switch
Replace expensive, opaque constraint bottlenecks.
Organizations lose time and money when constraint-heavy decisions take hours, fail without explanation, or cannot ship behind an API. Navokoj turns that bottleneck into a product surface.
Read the full switch narrative in Why customers switch to Navokoj.
Product contract
Model + deadline → verified decision.
Navokoj is an anytime constraint runtime. You do not wait for a black box to finish overnight. You get an inspectable result your application can act on.
Encode
Send Boolean CNF, weighted WCNF, schedule models, or finite-domain constraints that capture hard rules and soft preferences.
Bound
Attach a time budget and optional engine or hardware preference. The runtime optimizes under that deadline — not an open-ended batch.
Decide
Receive the best verified assignment available by the deadline, with status flags, residual violations, provenance, and billing metadata.
Result semantics buyers care about
- solved=true — every clause is satisfied
- feasible=true — all hard constraints are satisfied (soft may remain open)
- Partial / timeout — best-known assignment returned with residuals
- Provenance — engine, hardware, runtime, and billing in the response
{
"solved": false,
"feasible": true,
"assignment": { "nurse_3_shift_2": true, "...": "..." },
"residual_violations": [],
"runtime_ms": 148,
"engine": "nitro"
}Where it fits
Workloads technical buyers bring first.
Start with one expensive constraint decision. Measure baseline time, failure mode, and integration cost — then let the runtime earn a place in the stack.
Workforce & hospital scheduling
Shifts, skills, rest rules, and coverage must all hold — and the roster must ship before the next cycle.
- You send
- Schedule or CNF/WCNF model + deadline
- You get
- Hard-feasible roster with residual soft violations ranked
Logistics & allocation
Capacity, routing, and resource assignment under hard operational constraints.
- You send
- Boolean or finite-domain model of rules and objectives
- You get
- Best assignment available by budget, inspectable by ops
Verification & policy
Configuration, protocol, or circuit constraints where “maybe” is not good enough for hard rules.
- You send
- CNF / hybrid models with verification metadata requests
- You get
- SAT/feasible result plus provenance for audit trails
AI-agent planning & control
Agents need constraint-checked plans, not unconstrained tool loops.
- You send
- Planning or control-plane constraints as API workloads
- You get
- Deadline-bounded decisions agents can gate on
Put hard decisions behind an API.
Send a model and a deadline. Get an assignment your application can inspect and act on.
Constraint Execution API
Integrate constraint execution into your product. Submit a model and a deadline; Navokoj returns a decision your application can inspect, verify, and act on.
- Method: POST
- Endpoint:
/v1/solve - Input: Boolean, weighted, or finite-domain model
- Output: Decision + verification metadata
Built for
- Schedule: workforce and resource planning
- Verify: configuration and policy checks
- Decide: bounded, inspectable assignments
import requests
# 8 employees, 3 shifts, 7 days = 168 variables
payload = {
"num_vars": 168,
"clauses": [
# Employee 1 must work at least one shift
[1, 2, 3],
# Cannot work morning AND afternoon (Mutually Exclusive)
[-1, -2], [-2, -3], [-1, -3]
# ... more constraints
],
"engine": "nitro"
}
response = requests.post(
"https://api.navokoj.shunyabar.foo/v1/solve",
headers={"Authorization": "Bearer YOUR_KEY"},
json=payload
)Evidence you can inspect.
Selected results are linked to their artifacts, configurations, and verification records.
SUTRA constraint workloads
Production SUTRA engine • interactive Boolean solving
Hospital scheduling
Client-verified hard-feasible roster
Enterprise timetabling
Bounded-memory streaming execution
Finite-domain planning
Q-State execution at industrial scale
Gate-level circuit verification
Exact refinement with independent checker
Campaigns and configurations differ. Prefer the Hugging Face evidence ledger over isolated headlines.
Two Ways to Use Navokoj
Open Source Core + Production API
NitroSAT provides an open research and engineering release. Navokoj provides the managed runtime, routing, verification, and commercial execution surface.
Open Source
github.com/sethuiyer/NitroSATOpen-source SAT/MaxSAT research and engineering paths, including the V1, V2, and V3 solver lineage.
- ✓ Run SAT and MaxSAT workloads locally
- ✓ Work with large Boolean models and benchmark suites
- ✓ Stream large formulas with bounded memory
- ✓ Inspect assignments, results, and reproducibility artifacts
SUTRA Production API
navokoj.shunyabar.fooSUTRA is the production constraint engine behind the hosted runtime, with anytime results, diagnostics, verification metadata, and usage billing.
- ✓ Boolean, weighted, and finite-domain workloads
- ✓ Deadline-bounded best-known assignments
- ✓ CPU, GPU, repair, and streaming execution paths
- ✓ Verification-ready results and provenance
What the production API has solved
Engine lineage
From solver experiments to a production runtime.
Each stage added a different operating capability. Today, the API exposes the production SUTRA path through the stable engine: "nitro" contract.
Nano
Lightweight first-pass solving for small, fast requests.
Mini
Balanced in-memory solving for general API workloads.
Pro
Higher-quality production solving for mission-critical workloads.
NitroSAT
Open-source SAT/MaxSAT research and engineering release.
V2
High-throughput in-memory optimization for formulas that fit RAM.
V3
Streaming, incremental, bounded-memory execution for large formulas.
SUTRA
The production constraint engine behind Navokoj’s stable API runtime.
See it in action
Product overview
Watch how Navokoj returns deadline-bounded, inspectable constraint decisions for production workloads.
Deterministic, time-bounded constraint solving
Continuous dynamics and physics-inspired search for over-constrained systems where binary success/failure is not enough — and the deadline is real.
DEFEKT: pre-flight for constraints
Estimate difficulty before you spend a full solve budget. DEFEKT ranks likely conflict structure so you can route, debug, or avoid wasteful runs.
Avoid burning GPU minutes on workloads that look hopeless under budget.
Rank likely conflict groups and residual violations for human review.
Choose engine and hardware suited to the model and deadline.
Route to the engine and hardware best suited to this model and budget.
Start with a plan. Scale with compute.
Monthly workload entitlements, explicit rate limits, and usage-priced acceleration.
Hobbyist
Evaluate the runtime on small CPU workloads.
- 300 SAT solves / month
- 25 Q-State solves / month
- 10 schedules / month
- 10K variables and 100K clauses
- 1-request account ceiling; CPU access
Mini Lab
Build prototypes and low-volume production workflows.
- 2,000 SAT solves / month
- 250 Q-State solves / month
- 100 schedules / month
- 100K variables and 1M clauses
- 3-request account ceiling; CPU access
Launch Pad
Production APIs with Pro and L4 eligibility.
- 10,000 SAT solves / month
- 1,000 Q-State solves / month
- 500 schedules / month
- 1M variables and 8M clauses
- 10-request account ceiling; CPU + L4
Lotus Fleet
High-volume operation across every compute class.
- 50,000 SAT solves / month
- 5,000 Q-State solves / month
- 2,000 schedules / month
- 2M variables and 12M clauses
- 25-request account ceiling; CPU + L4 + H100
Compute settlement
Plan access first. Hardware usage second.
CPU entitlement is included in each plan. Overage and GPU execution draw from API credits.
$0$0.01 + $0.02/min$0.05 + $0.02/min$0.25 + $0.10/min$1.50 + $1.00/minDedicated capacity
More model size. More throughput. Your hardware.
Dedicated deployments are optimized for maximum model size and throughput. Limits are based on the hardware provisioned for your account rather than shared-cloud ceilings.
Private runtime
A premium deployment, not another shared tier.
- Dedicated infrastructure with no multi-tenancy
- Private API endpoint and private workload boundary
- Usage on the provisioned machine without shared-plan solve quotas
- No shared-cloud rate limits or concurrency throttling
- Custom solver configuration and deployment support
- Air-gapped operation available
Anytime runtime
A deadline returns a decision, not an empty wait.
Partial results include residual violations and provenance. Shared capacity has a 30-minute timeout; dedicated longer-running capacity is available by arrangement.
Developer access via GitHub Sponsors
Purchase Navokoj API compute credits through GitHub Sponsors. Sponsor ShunyaBar Labs to receive credits at 1.5x your sponsorship amount.
- Purchase credits via GitHub Sponsors.
- Email contact@shunyabar.foo with the transaction ID and your Navokoj account email.
- We provision or credit the account associated with that email.
Billing: compute time is measured per second. The API response and ledger are authoritative.
Canonical API contract
Plans, workloads, and hardware each set a limit.
The effective request limit is the lowest applicable value. This prevents a high-volume CPU entitlement from overrunning a reserved GPU queue.
Account plans
| Plan | Monthly | SAT / mo | Q-State / mo | Schedules / mo | Vars / clauses | Concurrent | Hourly | 30 sec |
|---|---|---|---|---|---|---|---|---|
| Hobbyist | $0 | 300 | 25 | 10 | 10K / 100K | 1 | 120 | 5 |
| Mini Lab | $19 | 2,000 | 250 | 100 | 100K / 1M | 3 | 1,000 | 15 |
| Launch Pad | $199 | 10,000 | 1,000 | 500 | 1M / 8M | 10 | 10,000 | 40 |
| Lotus Fleet | $499 | 50,000 | 5,000 | 2,000 | 2M / 12M | 25 | 50,000 | 80 |
Per-offering requests every 30 seconds
| Offering | Hobbyist | Mini Lab | Launch Pad | Lotus Fleet |
|---|---|---|---|---|
| Nano | 5 | 15 | 40 | 80 |
| Mini | 2 | 6 | 16 | 32 |
| SUTRA (`engine: nitro`) | 3 | 10 | 30 | 60 |
| Pro | - | - | 4 | 10 |
| Ensemble | - | - | - | 2 |
| Q-State | 2 | 4 | 8 | 16 |
| Scheduling | 1 | 2 | 4 | 8 |
| Diagnostics | 5 | 10 | 20 | 40 |
| Batch requests | 1 | 2 | 4 | 8 |
Hardware admission and queue ceilings
| Constraint metric | Standard CPU | L4 GPU | H100 GPU |
|---|---|---|---|
| 30-second request ceiling | 60 | 6 | 3 |
| Concurrent request ceiling | 8 | 3 | 2 |
| Boolean variables | 1,000,000 | 100,000 | 2,000,000 |
| Boolean clauses | 8,000,000 | 300,000 | 12,000,000 |
| XOR variables / constraints | 1,000 / 500 | 10,000 / 5,000 | 100,000 / 50,000 |
| Q-State nodes / states | 1,000 / 16 | 15,000 / 20 | 100,000 / 50 |
| Scheduling resources | 100 | 200 | 1,000 |
Account concurrency spans hardware pools; each pool also enforces its own ceiling. A batch consumes one
batch-request unit and one solver, account, hardware, and hourly unit per submitted model. GPU access is
plan-gated and usage-billed. GET /v1/pricing is the machine-readable source of truth for policy version, quotas, bursts, and prices.
Questions technical buyers ask
Result semantics, pilots, pricing, and verification—without the hype.
Developer access
Buy API credits. Ship a constrained decision.
Developer access via GitHub Sponsors: purchase Navokoj API compute credits through a developer-friendly payment rail. Sponsor ShunyaBar Labs to receive credits at 1.5× your sponsorship amount, then email the transaction ID and registration email for key provisioning.
Claim inbox: contact@shunyabar.foo · Careers: shunyabarlabs.github.io/careers