AI & Tech
Platform Ecosystem
The tools we use, the platforms we build, and the partners we trust to ship agentic systems at enterprise scale.
The Ecosystem
We don't build everything ourselves
The agentic ecosystem matures faster when teams stand on shared shoulders. We pick best-in-class tools where the market has converged, and we build proprietary components where our clients need a sharper edge than off-the-shelf can provide.
Below is a curated map of the platforms in our production stack today — what they do, why we chose them, and how they slot into the larger picture.
Foundation Models
The intelligence layer
Frontier
Anthropic Claude
Primary reasoning workhorse. Long-context analysis, nuanced writing, and tool use across complex chains.
Frontier
OpenAI GPT
Versatile generalist with strong tool calling. Often paired with structured output schemas for downstream parsing.
Open Weight
Meta Llama
Self-hosted in regulated environments where data residency or zero egress is non-negotiable.
Specialist
Fine-tuned domain models
Custom-trained on client data for narrow, high-volume tasks where smaller models beat frontier on cost and latency.
Multimodal
Google Gemini
Vision-heavy workloads — document parsing, screenshot analysis, and structured extraction from PDFs.
Embeddings
Voyage & Cohere
Domain-tuned embedding models that consistently outperform general-purpose alternatives in retrieval evals.
"The right model for the job changes monthly. The right architecture for swapping models doesn't."
Orchestration
Where workflows live
Apison Runtime
Our proprietary agent execution engine. Typed graphs, deterministic replay, durable checkpoints — purpose-built for enterprise workloads.
Inngest
Durable workflow scheduling for long-running agent jobs. Survives restarts, handles backoff, and gives us idempotency for free.
Temporal
Used in higher-throughput deployments where we need fine-grained control over saga patterns, cancellations, and signals.
LangGraph
Selectively used for graph-shaped agent topologies where its primitives map cleanly to client requirements.
Vector & Memory
Knowledge under the hood
pgvector on Postgres
Default for most deployments. Co-locates with relational data, supports hybrid search, and avoids the operational tax of a separate database.
Pinecone
Selected for high-cardinality workloads where serverless scale and metadata filtering performance matter most.
Turbopuffer
Cost-efficient option for cold-storage retrieval over very large corpora. Strong fit for archival and compliance workflows.
Letta & mem0
Long-term memory abstractions. Episodic, semantic, and procedural recall layered above raw vector storage.
Production footprint
30+
Distinct platforms in our hardened reference stack
99.95%
SLA target across orchestration plane
7
Cloud regions with active production deployments
Observability
Eyes on every agent
Langfuse
LLM-native traces with prompt, response, latency, and cost on every span. Self-hostable for sensitive deployments.
Datadog
Infrastructure metrics, APM, and log aggregation across the full surface. Pages on-call when budgets get blown.
OpenTelemetry
Vendor-neutral instrumentation underneath. Lets us swap backends without re-instrumenting the application layer.
Evaluation
Quality, regression-tested
Braintrust
Eval suites, dataset management, and side-by-side comparison of prompt or model variants.
Promptfoo
CI-friendly eval harness for regression gating and adversarial probe automation.
Apison Eval
Our internal harness for outcome-grounded business metrics — the kind that don't fit a generic framework.
Infrastructure
The substrate underneath
AWS, GCP & Azure
Multi-cloud by design. Client preference, data residency, or model availability — we deploy where the workload needs to live.
Kubernetes & Nomad
For self-hosted model inference and stateful agent runtimes that need predictable scheduling and graceful failover.
Terraform & Pulumi
Infrastructure-as-code is the only way we ship. Reproducible environments, drift detection, and signed deploys.
Cloudflare & Vercel
Edge delivery for client-facing surfaces. Low-latency routing into the agent plane for global user bases.
Curious how this stack maps to yours?
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