Agentic AI Systems
The product and agent layer: workflow architecture, MCP tools, scoped authorization, approval interfaces and human escalation.
Explore capabilityServices
Forward-deployed engineering for the whole AI product.
A forward-deployed team builds the agent platform or AI product with yours, from the first architectural decision to launch, then stays on monthly to run and improve it. We cover the product, the agent runtime and the cloud and data systems underneath.
The system behind the AI product
- Product experienceUser intent · approvals · human escalation
- Agent & tool layerRuntime · MCP · permission boundaries
- Evaluation & releaseEvidence · observability · rollback
- Platform foundationsIdentity · cloud · data access
Engineering capabilities
The right workstreams, assembled around your system.
Evals & Reliability
Acceptance evidence for the release: eval harnesses, retrieval quality, traceability, operational limits and recovery paths.
Explore capabilityPlatform Foundations
The systems underneath: identity, cloud environments, data architecture, secure integration and operational ownership.
Explore capabilityAI-Native SaaS / selected work
Agent Platform Engineering for Enterprise AI
- The problem
- Give AI agents a way to find, create and update a content platform's structured information.
- What we built
- Backend AI with Anthropic, OpenAI and Google models, 50+ MCP tools, content APIs and semantic search.
- What it made possible
- Agents that find information, act on it and power interactive experiences inside compatible AI clients, for a unicorn startup and Fortune 500 companies.
- 50+
- MCP tools built
Backend AI, API and infrastructure engineering, from architecture through launch.
Read case studyAgent platform engineering
- Backend AIAnthropic, OpenAI and Google
- 50+ MCP tools builtDiscover, create and update content
- APIs and searchStructured content and semantic retrieval
- Platform infrastructureSupports agents and MCP Apps
How to engage
Build it, then run it.
The forward-deployed build is the core engagement, and the monthly retainer keeps us on after launch. Reviews, diligence and fractional CTO work stand on their own or lead into a build.
The core engagement
Forward-deployed build
Initial three-month engagement
A forward-deployed team embeds with yours and builds the agent platform, AI product or the systems behind it. Scope, milestones and acceptance criteria are agreed before work starts.
Discuss a build How forward-deployed engagements workWhat the scope includes
Working software, the harness your engineers keep using with coding agents, evaluation and release gates, runbooks, and a handoff your team runs with.
Architecture, implementation and verification are planned together against agreed outcomes.
Agentic engineering runs through bounded tasks, verification and review. The agreed handoff includes the project’s guidance, checks and workflows, not just its code.
The proposal defines the workstreams, personnel, milestones, acceptance criteria, dependencies, tooling rights and transition. After launch, we can stay on a monthly retainer to run and improve the system.
Forward-deployed operations
Monthly retainer
After launch, we stay on to run the evaluations, keep the harness current as models change, respond to incidents and ship improvements.
Outputs: Evaluation and cost reporting, harness upkeep, incident response, ongoing improvements and a leadership readout.
How the retainer worksArchitecture & Harness Review
Two to three weeks
An independent read of your AI system or your team's agentic engineering workflow, ending in a prioritized plan.
Outputs: System or workflow map, risk register, evaluation and release plan, harness gap list, and a decision brief with the next scope.
Explore this optionTechnical & AI diligence
Two to four weeks
Evidence for an investment, acquisition or major platform commitment, including the real state of an agent-built codebase.
Outputs: Evidence-backed findings, material risks, integration and remediation plan, and a readout for the deal team.
Discuss diligenceFractional CTO
Initial three-month term
A senior technical counterpart for architecture, agent adoption and the decisions your board and investors ask about.
Outputs: Architecture decisions, agent-adoption plan, delivery reviews, and leadership and board readouts.
Explore this optionStart with a review or go straight to a build. Timing, access and acceptance are set in the proposal before work starts.
How we build
Agents implement.
Engineers own the result.
Harness engineering is how we prepare the context, tools, permissions and feedback around an agent. The delivery workflow adds architecture decisions, review and release ownership.
Every change runs through these gates. Your team receives the project guidance, checks and operating workflows alongside the software, so the speed carries over to your own engineers.
Explore the engineering methodThe software construction loop
01 / A bounded task
Define the outcome, acceptance criteria and exclusions. Prepare the repository context and allowed tools.
Start a conversation
What are you building—or deciding?
Tell us where you are. We reply within one business day, and the first conversation ends with a recommended next step.