Five disciplines. One delivery standard. Every engagement begins with a system audit, ends with a documented hand-off, and ships with monitoring on day one.
SRV_01
We design self-learning automation systems that absorb repetitive knowledge work — invoices, contracts, support tickets, internal lookups — and convert it into stable, audited pipelines. Every engagement begins with a workflow audit and ends with measurable hours-saved metrics.
Typical impact: 40–80% reduction in manual processing time.
Integrations: Salesforce, HubSpot, Zoho, Notion, Slack, Microsoft 365.
Tooling: Python, n8n, OpenAI, Anthropic, AWS Bedrock.
Typical SLA: 99.9% scheduled-job uptime.
Patterns: async workers, retry queues, idempotent jobs.
Stack: Python 3.12, FastAPI, Celery, Redis, Postgres.
SRV_02
When off-the-shelf tools hit their ceiling, we build the bespoke Python that takes over: scrapers that don't break, ETLs that don't lie, API integrations that survive vendor changes. Every job ships with observability, structured logs, and alerting baked in.
SRV_03
Designing the backbone of intelligent systems. We architect cloud-native ML platforms — feature stores, vector databases, training pipelines, GPU inference clusters — across AWS, GCP, and Azure. Reproducible from day one, with IaC, CI/CD, and cost guardrails baked in.
Cloud: AWS, GCP, Azure, bare-metal GPU.
Observability: Prometheus, Grafana, OpenTelemetry.
Compliance: SOC 2 - aligned, GDPR-conscious deployments.
Markets: Forex, XAUUSD, Indices, Crypto, US equities.
Platforms: MT4, MT5, cTrader, Binance, Bybit.
Process: walk-forward validation, monte-carlo stress, prop-firm rules.
SRV_04
Algorithmic execution at production grade. From idea to live deployment, we engineer Expert Advisors and crypto bots with strict risk envelopes, multi-session logic, and audited backtests. No curve-fitted promises — every system we publish includes its drawdown profile and worst-month statistics.
SRV_05
Conversational agents that earn their keep. We build LLM-powered bots for customer support, lead qualification, internal knowledge retrieval, and multi-step task execution. Citation-grounded by default; tool-calling where it matters.
Models: Claude, GPT, Gemini, Llama, Mistral.
Frameworks: LangChain, LlamaIndex, custom orchestration.
Eval: Ragas, deepeval, custom regression suites.
Tell us about the system you want to build. A senior engineer responds personally within one business day.
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