Give us
Give us one state-heavy workload, your current baseline, and the constraint that already hurts.
Evaluation access
The evaluation page is for edge, embedded, AI-at-the-edge, remote, robotics, industrial, IoT, defense-adjacent, and hardware-constrained teams that can name a baseline and a constraint worth solving.
Give us
Give us one state-heavy workload, your current baseline, and the constraint that already hurts.
We evaluate
We will evaluate where state movement creates waste and whether ATOMiK can improve the path.
You receive
You will receive a workload map, baseline comparison, evidence map, fit/no-fit recommendation, and next-step plan.
Success looks like
Success looks like a measured improvement against one agreed metric while preserving correctness and showing enough economic or technical value to justify a design-partner evaluation.
What to bring
You do not need to expose your entire product. Provide enough about one constrained state path to evaluate whether ATOMiK is relevant.
What ATOMiK evaluates
Metrics we can measure
Power, thermal, battery, footprint, and business-outcome claims stay diligence-only unless a responsible artifact supports the exact result.
| Metric | When it matters | Customer provides | ATOMiK evaluates | Meaningful result | Public safety |
|---|---|---|---|---|---|
| Bytes moved | Bandwidth-constrained links, radio duty cycle, sync-heavy paths | Current transfer volume, state size, update cadence | Compare full-state movement to meaningful state deltas | Fewer bytes moved for the same correct outcome | Homepage-safe as an evaluation target |
| Bytes avoided | Repeated sync, telemetry, agent context, remote systems | Baseline payloads, repeat/update traces, last-shipped state if available | Estimate or measure avoided transfers after coalescing and skip rules | Avoided bytes tied to bandwidth, cost, latency, or power budget | Proof-page-safe with artifact |
| Full-state transfers avoided | Systems that repeatedly send snapshots or rebuild full state | Snapshot frequency, object size, transport path | Identify where deltas can replace full-state movement | Fewer full transfers without losing correctness | Homepage-safe as an evaluation target |
| State scans avoided | Change detection that repeatedly asks what changed | Scan logic, region count, region size, scan cadence | Map scans to tracked regions and update boundaries | Fewer or cheaper scans against the same state path | Proof-page-safe with workload context |
| Replay or reconstruction cost | Log replay, local recovery, state rebuild, checkpoint restore | Replay path, event volume, reconstruction frequency | Measure work avoided by preserving meaningful transition state | Lower reconstruction cost while preserving final state | Proof-page-safe with artifact |
| Operations coalesced | Change-heavy workloads with repeated updates to the same regions | Operation trace or representative generator | Compare raw operations to unique state-region operations | Fewer emitted operations for equivalent state | Homepage-safe as an evaluation target |
| Unique-region ratio | Workloads where many logical operations hit fewer state regions | Region model, trace, update distribution | Measure touched regions divided by total logical operations | Low ratio signals stronger coalescing potential | Proof-page-safe with caveat |
| Cycles per update | Embedded processors, MMIO paths, local update loops | Cycle counter baseline and target hardware | Measure software, direct hardware, batched, and profiled paths where possible | Lower cycles/update on the selected path | Proof-page-safe with artifact |
| Update latency | Control loops, robotics, field systems, local state machines | Latency target, update path, timing method | Measure time from state change to usable updated state | Lower latency against the current baseline | Proof-page-safe with artifact |
| Response latency | AI-at-edge, robotics, user-facing embedded systems | End-to-end path and response target | Isolate whether state movement is on the response path | Lower response latency if state movement dominates | Diligence-only until measured |
| Duty cycle | Battery-limited and intermittently connected devices | Wake/sleep pattern, transfer cadence, power budget | Estimate whether fewer transfers or scans reduce active time | Reduced active duty cycle with responsible measurement | Diligence-only unless artifact-backed |
| Wake-up frequency | Radio-heavy IoT, sensor, and remote deployments | Wake events, sync schedule, radio or processor activity | Look for state paths that trigger unnecessary wake-ups | Fewer wake-ups tied to a device-level budget | Diligence-only unless artifact-backed |
| Memory/state footprint | Small devices, dense local state, constrained memory | State layout, memory budget, history/checkpoint strategy | Map stored state, deltas, and reconstruction requirements | Lower footprint pressure without losing required state | Proof-page-safe with artifact |
| Power proxy | Battery and thermal evaluations before instrumented power runs | Cycle counts, bytes moved, active time, power model if available | Use measured proxies until instrumented power data exists | Proxy improves enough to justify power-instrumented testing | Diligence-only unless clearly labeled |
| Thermal proxy | Enclosures, dense racks, fanless devices, field reliability | Utilization, cycles, transfer volume, thermal limit | Use workload proxies to decide whether thermal measurement is worth running | Proxy reduction that supports a thermal test plan | Diligence-only unless measured |
| Bandwidth pressure | Expensive, intermittent, congested, or tactical links | Baseline bandwidth, link budget, transfer frequency | Compare baseline transfer pressure to state-aware transfer pressure | Less pressure on the constrained link | Homepage-safe as an evaluation target |
| Correctness preservation | Every evaluation | Expected outputs, invariants, test oracle, acceptance criteria | Verify that reduced movement or coalescing preserves required state | Same correct state or accepted behavior after optimization | Homepage-safe |
| Target business outcome | Continuation decisions and paid evaluations | Decision threshold, budget owner, economic or technical value | Connect measured improvement to the constraint that already hurts | Enough value to justify design-partner, licensing, or diligence work | Diligence-only for customer-specific numbers |
Step-by-step process
Step 1
Confirm one measurable constraint, confirm the workload is state-heavy, and route to proof review, technical evaluation, licensing, investor diligence, or no-fit.
Step 2
Anchor on one workload, identify the current baseline and painful constraint, choose one primary success metric, and decide whether an NDA is needed.
Step 3
The customer provides enough about one constrained state path to evaluate relevance without exposing the entire product.
Step 4
ATOMiK looks for full-state movement, repeated scans, repeated replays, avoidable reconstruction, and opportunities for deltas, coalescing, local reconstruction, or cleaner state-transition boundaries.
Step 5
Before benchmark or prototype claims, define the baseline, measurement method, success metric, threshold, evidence tier, and decision the result will support.
Step 6
Pick the right path: proof review, software exploration, benchmark exchange, workload mapping, hardware-backed demo, technical evaluation, design-partner evaluation, licensing/IP diligence, or investor diligence.
Step 7
Deliver the workload map, baseline comparison, evidence/proof map, results or evaluation plan, fit/no-fit recommendation, risks, claim boundaries, and next-step recommendation.
Step 8
The result can be no fit, proof review complete, technical evaluation recommended, design partnership recommended, licensing/IP diligence recommended, or investor diligence recommended.
What you receive
What success looks like
ATOMiK is successful for a customer evaluation when it improves the pre-agreed metric against the current baseline, preserves correctness, and connects that improvement to a business constraint worth pursuing.
Fit signals
The workload repeatedly moves, scans, syncs, replays, or rebuilds state.
The team can provide a current baseline and a decision threshold.
Battery, heat, bandwidth, latency, footprint, weight, reliability, or cost is already painful.
Correctness can be checked against an expected state, invariant, or output.
The economic or technical value is large enough to justify evaluation work.
No-fit signals
There is no measurable constraint.
The workload is mostly stateless compute.
The customer cannot share even representative state behavior.
The baseline is unknown and cannot be measured.
Correctness cannot be verified.
The claimed pain is not expensive enough to support evaluation.
Reserve or request
Reservation
For: Teams, investors, and technical evaluators who need a proof-bound review before a deeper evaluation.
Reserve focused review time around one workload, one constraint, and the evidence needed to decide whether ATOMiK is worth deeper evaluation.
Reservation
For: Teams with a real state-heavy workload, current baseline, and budget owner for heat, power, bandwidth, latency, footprint, reliability, or compute-density pressure.
Start a focused evaluation track with workload mapping, success criteria, and an evidence plan before any larger design-partner commitment.
Strategic track
For: Chip, embedded, infrastructure, and strategic partners evaluating ATOMiK as architecture or embeddable IP.
- Proof-bound IP and artifact review
- Hardware and synthesis evidence map
- ASIC feasibility and integration-risk discussion
- Licensing or strategic partnership next-step plan
Strategic track
For: Investors reviewing the transition from proof to evaluated customer/IP opportunities.
- Investor brief and evidence map
- Claim boundaries and proof packet
- Paid-evaluation and design-partner strategy
- IP protection and ASIC feasibility review
Proof boundary
- Universal speedup
- Guaranteed battery extension
- Guaranteed heat or cooling reduction
- Guaranteed water or power-bill savings
- Guaranteed smaller hardware or footprint
- Generic better compute
- Proof from unrelated workloads
The best fit is Edge and embedded teams that can provide one representative state-heavy workload, one current baseline, and one painful constraint expensive enough to evaluate.
ATOMiK follows up to anchor the conversation on one workload, one current baseline, one painful constraint, one primary metric, and the evidence required for a decision. Larger engagements are scoped in writing.
Not always. The first pass can use pseudocode, synthetic traces, sanitized logs, or representative state behavior. NDA is appropriate when the constrained state path cannot be evaluated responsibly without sensitive details.
This is not generic self-serve product access, a guaranteed production integration, or a promise of universal speedup, battery extension, heat/cooling reduction, water or power-bill savings, footprint reduction, or smaller hardware.
Measured, hardware-validated, software-validated, synthesis-validated, build-artifact, projected, conceptual, and roadmap claims are labeled separately and linked to artifacts when used publicly.