OBS / M57Senior software systemsGovernment + industry

Systems that survive contact with reality.

m57labs scopes, designs, and ships custom software, data systems, and applied AI—with the same senior engineers staying in the loop.

Start a scoped conversationView the evidence

Two commercial platforms designed, built, and deployed by this team.

Image: ESA/Webb, NASA, CSA, M. Barlow, N. Cox, R. Wesson · crop/color treatment ↗
Team topologySenior / direct
Translation layersZero
Commercial systems02 deployed
Operating modeContext intact

Transmission / capabilities

  • Custom software engineering
  • Web & mobile applications
  • Data platforms & APIs
  • Applied AI, automation & assurance
  • Legacy modernization
  • Cloud architecture

01 / THE ENGAGEMENT GAP

Context is the critical system.

Software drifts when decisions pass through sales, account layers, and disconnected delivery teams. We keep the signal attached to the people responsible for the outcome.

  1. 01handoff / 0

    Context stays attached

    The engineers in the first conversation remain close to the decisions, the code, and the deployed result.

  2. 02continuity / on

    Change without the cliff

    We modernize aging workflows in credible increments without gambling the operation on a big-bang rewrite.

  3. 03audit / visible

    Automation you can inspect

    AI is built with explicit boundaries, failure paths, human controls, and behavior the operating team can audit.

  4. 04lifecycle / owned

    Built for the day after

    Architecture, deployment, operating cost, and maintenance are part of the build—not a hand-off at the end.

02 / PROOF OF BUILD

Not decks. Deployed systems.

Two commercial platforms engineered by the same team—from system model through production deployment.

  1. CASE / 01atriam.aiVERIFY ↗

    Atriam

    Construction operations platform

    Scheduling, field reporting, and document workflows — designed, built, and deployed by this team as a commercial product.

    • System architecture
    • Product engineering
    • Production deployment
  2. CASE / 02sitecall.aiVERIFY ↗

    SiteCall

    AI communications platform

    Voice AI for inbound calls — speech, routing, and workflow automation engineered in-house.

    • System architecture
    • Product engineering
    • Production deployment

03 / AI ASSURANCE

AI assurance, with evidence attached.

A local-first control and evidence layer for AI-enabled systems—built for teams that need an inspectable record, not a mystery score.

Supports control-level evidence review. Does not certify compliance or replace legal, privacy, security, acquisition, or authorized-official review.

Available for a scoped pilotExplore the workbench
M57 / ASSURANCE / LOCALHUMAN AUTHORITY

m57-assure verify m57-assurance.json

SAMPLE MANIFESTBenefits document assistantpilot · high impact · local evidence
  1. SATISFIEDGV-01

    System ownership + intended use

  2. SATISFIEDMP-02

    Data categories + handling

  3. SATISFIEDMS-01

    Intended-use evaluation

  4. SATISFIEDMG-02

    Incident response + rollback

CONTROL-LEVEL FINDINGSJSON + MARKDOWN + OSCAL PREVIEWNO COMPLIANCE SCORE
  1. 01catalog / 2026.07

    Control registry

    Versioned control IDs, applicability rules, evidence requirements, and remediation guidance.

  2. 02human / explicit

    Interactive TUI

    A local review workspace for scope, findings, evidence confidence, reassessment triggers, and exports.

  3. 03agent / bounded

    Structured MCP

    Root-confined reads and proposal-only drafts for agents—without evidence mutation, shell access, or network access.

LOW-RISK ENTRY / SCOPED PILOT

One AI-enabled workflow. One reviewable evidence pack.

Start with a bounded system and leave with an inventory, control map, evidence gaps, and working interfaces your team can inspect.

DELIVERABLES

  • System inventory
  • Control mapping
  • Evidence gap register
  • TUI + MCP integration
  • Immutable buyer-review bundle

BUYER REVIEW PACK

  • Intended-use and impact rationale
  • Model, vendor, and data inventory
  • Human oversight and escalation paths
  • Evaluation, monitoring, and incident evidence
  • Local-first evidence handling

Initial traceability references the NIST AI RMF, its Generative AI Profile, and current federal AI governance and LLM procurement context, including OMB M-26-04. References are not claims of conformance.

04 / FIRST ORBIT

Start with the real constraint.

A useful first step does not need a six-week discovery phase. It needs the right people looking at the real system together.

  1. Signal

    Locate the real constraint

    Bring the users, the stuck workflow, and what must change. A polished brief is not required.

  2. Trajectory

    Define a credible first orbit

    We align on architecture, constraints, and the smallest useful increment before expanding scope.

  3. Contact

    Build with the same people

    The senior engineers who shaped the approach stay through implementation, deployment, and change.

05 / BEFORE CONTACT

Clear before we connect.

Senior people, direct communication, and a strong preference for concrete software problems.

01What kinds of systems do you take on?

Custom web and mobile applications, data platforms and APIs, applied AI and automation, legacy modernization, and the cloud architecture needed to deploy them.

02Do you only build new products?

No. We can build a new system, integrate with an existing stack, or replace an aging workflow incrementally when continuity matters more than a clean-sheet rewrite.

03How do you approach AI work?

As software engineering, not a demo. We define system boundaries, failure paths, human controls, and auditability alongside model behavior and workflow automation.

04Does the assurance toolkit certify compliance?

No. It creates a control-level evidence record, identifies gaps, and makes findings reviewable. Legal, privacy, security, acquisition, and authorized-official determinations remain with the responsible people.

05What can an AI agent access through MCP?

Root-confined assurance reads plus proposal-only drafts for evidence links, exceptions, and review requests. The MCP server cannot apply those drafts, mutate evidence, accept risk, sign decisions, run shell commands, or use the network.

06Can you support government and prime-contracting conversations?

Yes. The capability statement summarizes our services, classifications, differentiators, and built-and-deployed product work in a format that is easy to circulate internally.

07What happens after the first email?

We schedule a focused fit conversation around the users, constraints, current system, and desired outcome. If the work is outside our fit, we say so early.

08Who owns the work?

Engagement terms define ownership explicitly. Our default posture is to make the system maintainable and understandable by the team that will live with it.

OPEN CHANNEL / READY

Bring the real problem into view.

Send the users, the stuck workflow, and the outcome you need. We will tell you directly if we are the right team to solve it.

Start a scoped conversationReview capability statement first